IT Content Writer with 12 years of professional writing experience. Prefers facts and figures to any kind of fiction.

Dominika Reszke

<p><strong>Rust vs Go is one of the most interesting oppositions in modern software development. Also, it’s one of the most important decisions for programmers to make.&nbsp;</strong></p><p>As <a href="https://insights.stackoverflow.com/survey/2021" target="_blank" rel="nofollow">The Stack Overflow 2021 Developer Survey</a> unveiled, out of over 80,000 developers who took part in it, over 10,000 JavaScript developers want to start or continue developing in Go or Rust. Moreover, Rust is dubbed the most loved language for the sixth year running, with almost 87% of indications in the year 2021.</p><p>But can any of these highly appreciated programming languages be regarded as better, in fact? Well, the above-mentioned Stack Overflow survey shows that utilizing them lets software developers earn similar yearly remuneration, accounting for $77,530 in the case of Rust, and $75,669 as far as Go is concerned.</p><p>Of course, this is just the beginning of the long list of what Go and Rust have in common. But this doesn’t mean that there are no differences in the Rust Go combo. In this article, we’ll try to help you decide whether you should go Rust or maybe try Go instead in the nearest future.</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#rust-intro">Isn’t Rust a bit rusty? All you need to know about it</a></p><p>2. <a href="#go-intro">Is Go worth a Go? What makes it useful?</a></p><p>3. <a href="#comparison">Rust vs Go – which one is better?</a></p><p>4. <a href="#use">Rust or Go? Find the perfect match for your project</a></p><p>&nbsp;</p><div class="raw-html-embed"><section id="rust-intro" style="height: 20px;"></section></div><h2>Isn’t Rust a bit rusty? All you need to know about it</h2><p>As already mentioned, Rust is being chosen on and on as the most loved programming language by developers surveyed by Stack Overflow. Undoubtedly, those repeated results over the years mark a huge success of this programming language, considering that this environment changes rapidly, and there are more and more competitors showing up regularly.</p><p>But where does this affection come from?</p><p>Well, what makes Rust fans love it are features such as impressive performance, memory safety, safe concurrency, cutting-edge tooling, great documentation, and useful appliances such as auto-formatter, auto-completion, and other supporting functions.</p><p>Boiled down, Rust is a high-level, general-purpose, cross-platform, multi-paradigm, concurrent, and functional programming language. What’s also crucial in terms of Rust code or Rust programs is that Rust is syntactically similar to C++.</p><div class="raw-html-embed"><section id="go-intro" style="height: 20px;"></section></div><h2>Is Go worth a go? What makes it useful?</h2><p>And what can be said about Go? In short, Go is a statically typed, object-oriented, concurrent, and functional programming language. Also, Go belongs to compiled languages, which makes it comply with machine code easily (with no additional installations necessary) and outperforms interpreted languages. Sometimes it is referred to as Golang although this is not correct as Golang.org is just Go’s domain name and not this language’s legitimate name.</p><p><a href="https://golang.org/" target="_blank" rel="nofollow"><u>On its website</u></a>, Go calls itself „an open source programming language that makes it easy to build simple, reliable, and efficient software”. Many users also praise it for being easy to read and easy to comprehend. Other interesting features include scalability, flexibility, automatic memory management, powerful error checking, as well as detecting variables that go unused and impressive speed.</p><div class="raw-html-embed"><section id="comparison" style="height: 20px;"></section></div><h2>Rust vs Go - which one is better?</h2><h3>Rust &amp; Go similarities</h3><p>The list of Rust and Go similarities seems to be endless. They are nearly age-mates, with Go first appearing in <a href="https://en.wikipedia.org/wiki/Go_(programming_language)" target="_blank" rel="nofollow">November 2009</a>, and Rust debuting only a few months later, in <a href="https://en.wikipedia.org/wiki/Rust_(programming_language)#cite_note-mozilla-research-18" target="_blank" rel="nofollow"><u>July 2010</u></a>. They both have huge corporations standing behind them – Google in the case of Go, and Mozilla as far as Rust is concerned. They even have their own mascots – Ferris is the (unofficial) one of Rust, and the famous Gopher is associated with Go.</p><p>Both Go and Rust are compiled, concurrent, and multi-paradigm system programming languages, perfect for supporting parallel computing environments.</p><p>&nbsp;</p><h3>Rust vs Go key differences</h3><p>Rust alone is famous for its exceptional run speed, being secure, well-designed, and offering many advanced yet practical features. Also, it has a useful inbuilt dependency and build management. Moreover, software developers can take advantage of a vast Rust community support and make use of <a href="https://doc.rust-lang.org/book/index.html" target="_blank" rel="nofollow"><u>The Rust Programming Language</u></a> book. However, despite having access to those resources, some users say Rust was not that easy to learn as it has a steeper learning curve than Go.</p><p>In turn, Go’s advantages include simple language syntax, outstanding code readability, great ecosystem, community support, and a variety of libraries available. On the downside, Go may be regarded as oversimplified and a little superficial, and this may imply some limitations of its use.</p><p>Moreover, the fact that Go forces a garbage collection run no less often than every 2 minutes can cause problems such as <a href="https://discord.com/blog/why-discord-is-switching-from-go-to-rust" target="_blank" rel="nofollow"><u>latency spikes, worsened user experience</u></a> as well as failing to meet performance targets. Rust, on the other hand, has no runtime or garbage collector, and this makes it „blazingly fast and memory-efficient”, <a href="https://www.rust-lang.org/" target="_blank" rel="nofollow"><u>as it calls itself on its website</u></a>.</p><p>For this reason, Rust’s memory management is outstanding with memory security guaranteed and memory used by the program being freed when it is not needed anymore, and with no runtime memory safety bugs. Rust itself highlights the fact that its ownership model and rich type system „guarantee memory-safety and thread-safety”.</p><div class="raw-html-embed"><section id="use" style="height: 20px;"></section></div><h2>Rust or Go? Find the perfect match for your next project</h2><p>Being aware of the pros and cons, or advantages and disadvantages of utilizing both Go and Rust makes software developers more confident in making decisions regarding choosing any of these. But can we indicate a winner in the „Golang” vs Rust opposition? Well, in the major Golang vs Rust performance category, Rust takes the lead, as it is regarded as way more efficient and offers better execution speed and development speed. However, it may be a little worse than Go <a href="https://codersera.com/blog/go-vs-rust/" target="_blank" rel="nofollow"><u>when compilation speed is concerned</u></a>.</p><p>In the case of Go, simplicity rules, and many modern conveniences simply aren’t there. It is great, however, for writing code for lightweight microservices or single-page apps, as well as for writing clear API server code fast. It’s also right to learn as a complementary language for software developers who already have some experience with other languages (and switching to it from Python, C/C++, or JavaScript, for instance, may be a good idea).&nbsp;</p><p>You can go from C or C++ to Rust, too, and succeed similarly. Rust, in general, can be a great fit for many use cases as it is a general-purpose and low-level language. Some of its use cases include browser engines, <a href="https://codilime.com/blog/why-is-rust-programming-language-so-popular/" target="_blank" rel="nofollow"><u>operating systems, microcontroller applications</u></a>, distributed online services, and embedded devices. Undoubtedly, it has great potential, and is ahead-of-time, loved by young software developers, and is definitely worth giving it a try in the year 2021.</p><p><strong>And to you, which one is a better choice for 2021’s challenges – Go or Rust? And what makes the chosen language better or more appropriate than the other one? What are its main advantages software developers can utilize in their day-to-day work?</strong></p>

Rust vs Go: Which One Is a Better Choice in 2021 | Codete Blog

Go vs Rust: Which One Will Be a Better Choice in 2021?

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<p>One of the best things about <internallink internallinkid="/blog/type-script-vs-java-script-which-one-to-choose-for-2021-web-applications">JavaScript</internallink> is that it comes with many different libraries that developers can use for solving practically any problem – including data visualization, a common element of many applications today.</p><p><strong>Data visualizations</strong> help to simplify how we work with and understand data, which is critical for many applications that rely on it. Luckily, developers building such solutions can take advantage of many data visualization libraries.</p><p>In this article, we will take a closer look at <strong>data visualization solutions available in JavaScript</strong> to show you why using them is a good idea. Here’s a list of 12 most common such tools to help improve your software development process.</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#intro">Why should you use JavaScript data visualization libraries?</a></li><li><a href="#libraries">What's the best JavaScript data visualization library for your project?</a></li><li><a href="#wrap-up">Now you know everything about JavaScript data visualizations</a></li></ol><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>Why should you use JavaScript data visualization libraries?</h2><p>Picking the right style for displaying data so that it’s readable and understandable – this is a critical step in any application design today.</p><blockquote><p><strong>Data visualization</strong> is a combination of art and science. It’s an umbrella term for all the methods used to deliver the insights from data analysis. Take a look around and you’ll see that practically every application on the market requires or uses data in some way to enhance its functionality.</p></blockquote><p>Consumers like tracking their activities and data visualization streamlines the process of understanding the data better. Many applications allow users to share insights with others – and this is where data visualization tools come in handy as well. By using them, developers can make data more readable and increase the user’s ability to analyze data visually.</p><div class="raw-html-embed"><section id="libraries" style="height: 20px;"></section></div><h2>What's the best JavaScript data visualization library for your project?</h2><h3>1. React-vis</h3><p>This library was developed by a team at Uber for creating React visualizations. Uber is still the largest organization that supports that library. The React-vis library is very simple to install and use. It also comes with great documentation backed by Uber. It features all the popular charts like line, bar, pie, treemaps, and more.</p><p>The good thing about this library is that you don’t need any prior knowledge of any other library. Instead, you can instantly use modular low-level building blocks such as the XY axis to create your visualizations. It’s a good fit for working with <a href="https://codersera.com/blog/javascript-data-visualization-libraries/" target="_blank" rel="nofollow">Bit</a>.</p><p>Key features:</p><ul><li>Easy to use and doesn’t require prior knowledge of data visualization packages.</li><li>Flexible, robust, and based on modular building blocks.</li><li>Comes with a set of default elements that can be customized.</li><li>Integrates really well with React.</li></ul><p>&nbsp;</p><h3>2. D3.js</h3><p>&nbsp;This data visualization JavaScript library is most commonly used to manipulate documents that are based on data. It uses web standards and works with JavaScript <internallink internallinkid="/blog/most-popular-front-end-frameworks-in-2021">frameworks</internallink> like React or Vue. Today, it’s one of the most popular data visualization packages on the market and many other libraries are actually based on it.&nbsp;&nbsp;</p><p>D3 uses modern web standards like SVG, HTML, and CSS. With D3, you don’t need any standard visualization formats. You can use it to build graphs, HTML tables, geospatial maps, bar charts, and pie charts.</p><p>Key features:</p><ul><li>Robust and flexible.</li><li>Fast and easy to use.</li><li>Supports large data sets.</li><li>Uses declarative programming.</li><li>Provides the transition() function.</li></ul><p>&nbsp;</p><h3>3. VX</h3><p>VX is a collection of low-level visualization components that developers can reuse to create stunning data visualizations quickly. In order to update the DOM, VX uses the functionality of D3 for producing visualizations with the extra benefits coming from React.</p><p>The idea here is to build a component library that can be used to develop a reusable chart library and customize charts. VX is opinionated and works as a simple collection of reusable components. Under the hood, VX uses D3 for mathematical calculations. When building a chart library on top of VX, developers can create an API component that will fully hide D3.</p><p>Key features:</p><ul><li>Easy to access and use.</li><li>Ability to create complex graphs.</li><li>Excellent API.</li><li>Offers unique transitions and animations.</li></ul><p>&nbsp;</p><h3>4. Chart.js</h3><p>This open-source JavaScript library allows developers to leverage the HTML canvas feature and create various types of charts. Since the library needs canvas, it’s necessary to use a polyfill to support older browsers.</p><p>The library offers six major chart types by default, facilitating their usability. It’s very easy to understand even for someone without much experience in this area. Developers get a selection of completely responsive charts like line, radar, scatter, pie, bar, bubble, doughnut, or polararea. Developers can also mix different line and bar charts to incorporate different data sets into a single chart.</p><p>Key features:</p><ul><li>A great choice for huge data sets.</li><li>Open-source library available free of charge.</li><li>It offers lots of built-in charts.</li><li>Default charts can be easily customized.</li><li>It supports modern browsers.</li><li>It’s built on top of Canvas (works well with large datasets).</li></ul><p>&nbsp;</p><h3>5. TradingVue.js</h3><p>This handy charting library is a great choice for developers who want to draw customized designs on top of candlestick charts. They especially come in handy for trading applications. Using the library, it’s easy to build custom indicators and map data to screen coordinates. All the things like scrolling, reactivity, and scaling happen behind the scenes.</p><p>Key features:</p><ul><li>Scrolling and zooming.</li><li>Basic API for creating new overlays.</li><li>It offers a completely reactive and responsive design.</li><li>It provides customized drawing tools.</li><li>An excellent choice for trading apps because it’s extremely fast - it works even as fast as 3 mil candles.</li></ul><p>&nbsp;</p><h3>6. ReCharts</h3><p>ReCharts is a library that uses D3 under the hood to demonstrate the declarative components. It’s pretty light and renders SVG elements excellently, allowing devs to build interactive charts easily. Developers can easily modify the charts to create customized designs.</p><p>If you’re looking to create a static chart, the library comes in handy as well because it offers a great output and built-in general chart resources such as legend tooltips and labels. And if you need to create a chart with huge data sets, it will handle your use case.</p><p>Key features:</p><ul><li>Enables developers to build charts with the coupled and reusable react components.</li><li>Lightweight and reliable.</li><li>Composable charting library.</li><li>Offers a powerful and responsive feature with an intuitive API.</li></ul><p>&nbsp;</p><h3>7. Victory</h3><p>Victory is a set of components for modular charting that are especially helpful for React and React Native. The library does a good job of making a chart by offering developers fundamentals they can use in developing visualizations.</p><p>The library features concepts like labels, customizing access, and using different data sets for particular graphs. Customizing styles and behavior is very simple as well. It comes in handy especially for cross-platform applications and allows developers to build attractive graphs with low code.</p><p>Key features:</p><ul><li>Features easy-to-use components that handle complex targeting.</li><li>Comes with reusable data visualization elements used for their own styles and behaviors.</li><li>Works with React Native (mobile applications).</li><li>It’s robust and flexible.</li></ul><p>&nbsp;</p><h3>8. Echarts</h3><p>This JavaScript library works for the browser Baidu’s eCharts project. It uses proper JavaScript and is centered around the zrender canvas library. As a result, developers can use it for rendering charts in the manner of Canvas, VML, and SVG.</p><p>Echarts is also handy for powerful server-side rendering with node-canvas on the node. The library provides a selection of basic chart types - from bar series and box lot to candlestick, heatmaps and more.</p><p>Key features:</p><ul><li>The library is optimized for mobile interactions.</li><li>It makes the zoom function easier to handle.</li><li>You can use it to display visualizations of a lot of the big data sets.</li><li>It supports multidimensional data.</li></ul><p>&nbsp;</p><h3>9. Frappe Charts</h3><p>This is a basic library for building charts without any dependencies. It’s a GitHub-like visual package that supports bar, line, and other chart styles. Developers can also use it to build heatmaps.</p><p>Key features:</p><ul><li>Open-source.</li><li>SVG-based.</li><li>It’s responsive and easy to use.</li><li>It has a small bundle size.</li></ul><p>&nbsp;</p><h3>10. Nivo</h3><p>This unique framework is built on top of React and D3. In total, it offers 14 different components you can use to display your data. When it was launched in 2017, it gained success after being featured on Product Hunt as the product of the day.</p><p>Nivo offers developers many different customization choices and three different ways to render: HTML, Canvas, and SVG. It’s a great choice for creating visualizations that are both customizable and attractive.</p><p>Key features:</p><ul><li>High level of customization.</li><li>Great and exhaustive documentation.</li><li>It includes motion and transitions that are driven by react-motion.</li><li>Great for responsive design.</li></ul><p>&nbsp;</p><h3>11. Google Charts</h3><p>This is a well-known solution for charts used by JavaScript developers. As a JavaScript library, it offers chart forms like bar, geo, area, and others. While the library is free to use, it’s not open source. Also, it’s not responsive – however, developers can use code so that it resizes the charts. Depending on the chart type, you can choose from different customization options.</p><p>Key features:</p><ul><li>Offers a rich gallery of charts.</li><li>Provides great customization.</li><li>Comes with HTML and SVG properties.</li><li>Brings developers dashboards, controls, and free chart tools.</li><li>Developers can modify charts even after chart generation.</li></ul><p>&nbsp;</p><h3>12. Zoom Charts</h3><p>Another popular data visualization library is Zoom Charts. Apart from its reactivity, it brings developers multitouch gestures and great experience across any kind of device. The library is full of beautiful visualizations that require minimal code from developers.</p><p>Your team can easily implement them on any device. The library is based on canvas and one of the key benefits is that it runs even 20 times quicker with its default settings than other SVG-based counterparts.</p><p>Key features:</p><ul><li>Developers can create visually rich and interactive charts for applications.</li><li>It’s easy to learn and onboard.</li><li>It requires a minimal amount of code writing.</li><li>It allows developers to discover new insights and data.</li></ul><p>&nbsp;</p><div class="raw-html-embed"><section id="wrap-up" style="height: 20px;"></section></div><h2>Now you know everything about JavaScript data visualizations</h2><p>Developers can choose from many different libraries that allow visualizing data easily. Since JavaScript is only becoming more popular on the data visualization scene, the market is surely going to expand and offer devs even more tools they can use for creating beautiful charts for web applications.</p><p>We hope that this article gave you a good idea of what’s out there and which potential libraries you could use for your next project.</p><p><strong>Have you used any of these libraries already? Are you planning to? Give us a shout-out in the comments and share your thoughts about JavaScript data visualization libraries that make our lives easier and help us to create some beautiful charts at the same time.</strong></p>

​​12 JavaScript Data Visualization Tools to Know in 2021 | Codete Blog

​​12 JavaScript Data Visualization Tools to Know in 2021

<p>While it may be clear why Java language is often labeled as secure, simple, dynamic, portable, and reliable as well as class-based and object-oriented, the answer to the question of why Java is platform independent may not be that obvious.&nbsp;</p><p><strong>„Java platform independent”</strong> is a phrase that is often searched within search engines as it may not be clear what this term actually means. But „platform independence” simply implies independence from all types of platforms. The code can also run on all operating systems.</p><p>In this article, we’ll zoom in on Java’s platform independence.</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#intro">Java and platform independence</a></p><p>2. <a href="#reasons">Things that make Java platform independent</a></p><p>3. <a href="#use">Why using Java in your projects might help</a></p><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>1. Java and platform independence</h2><p>Java is an open-source, high-level (easy to understand for programmers, and thus not a low, machine-level language easy to understand primarily for computers), reliable, secure, multithreaded, and versatile programming language. It can also be referred to simply as a Java program or, more elaborately, as a <a href="https://en.wikipedia.org/wiki/Java_(software_platform)" target="_blank" rel="nofollow">set of computer software and specifications</a>.</p><p>Apart from many other characteristic features it is known for, like being object-oriented or class-based, the Java programming language is platform independent or a cross-platform one. But what exactly sets it apart from platform dependent programming languages?</p><blockquote><p>Well, first of all, being a programming language with a low number of implementation dependencies, with compiled Java code able to run „<a href="https://en.wikipedia.org/wiki/Java_(programming_language)#cite_note-design_goals-18" target="_blank" rel="nofollow">on all platforms that support Java without the need for recompilation</a>”, was at the very core of Java’s design back in the 1990s. Its founding, in 1994, is credited to a Canadian <a href="https://en.wikipedia.org/wiki/James_Gosling" target="_blank" rel="nofollow">James Gosling</a> – also known as Dr.Java or simply dubbed the father of Java – of Sun Microsystems at that time.</p></blockquote><p>Interestingly, the platform independent Java runs on the Java Virtual Machine (JVM) which is… platform dependent, as there are different versions needed for particular operating systems. In general, the term „platform dependent” usually refers to applications <a href="https://www.pcmag.com/encyclopedia/term/platform-dependent" target="_blank" rel="nofollow">that run under only one operating system in one series of computers</a>” but may also mean „machine dependent” or „hardware dependent”.</p><div class="raw-html-embed"><section id="reasons" style="height: 20px;"></section></div><h2>2. Things that make Java platform-independent</h2><p>Now, what makes the Java platform independent? Let’s go through a couple of reasons.</p><blockquote><p>In general, platform independence may be called a <a href="https://wiki.c2.com/?PlatformIndependence" target="_blank" rel="nofollow">technology that allows programmers to reuse things</a> that had been initially implemented on one machine on others – without the need to apply any major changes prior to or related to that.&nbsp;</p></blockquote><p>In other words, the Java Byte Code written on one occasion and on one machine may be run on another one, which offers a proper environment for it, at any time.</p><p>But the machine usually needs a machine-level language that it can comprehend. For this reason, a compiler or converter that translates high-level language Java is into one understood by machines is necessary. As a result of this operation, source files ending with the .java extension are easily transformed into .class files (executed by JVM). Any platform that runs JVM (that gets installed automatically along with Java) can be used for Java source code execution.</p><p>This way, the source code (written in plain text files) is turned into an executable one – which can be <a href="https://www.geeksforgeeks.org/java-platform-independent/" target="_blank" rel="nofollow">performed with the help of Java Byte Code</a>. Thus, the latter – a highly optimized set of instructions – may be regarded as the core of Java’s platform independence.</p><p>But why Java is a platform independent language is one thing, and why it may be worth using it in your projects is another.</p><div class="raw-html-embed"><section id="use" style="height: 20px;"></section></div><h2>3. Why using Java in your projects might help</h2><p>Java is a platform independent language, but also an object-oriented, class-based, and generic one. Moreover, it is known as general-purpose language so its use cases are quite diverse. It is broadly applied across many domains and used for a variety of development tasks. The list of Java’s use cases is impressive and embraces things such as creating Android apps, games, and websites, including those of high-profile corporations, like <a href="https://data-flair.training/blogs/java-use-cases/" target="_blank" rel="nofollow">Google or LinkedIn</a>, as well as <a href="https://medium.com/javarevisited/8-best-popular-projects-on-java-e1a663ab3cc1" target="_blank" rel="nofollow">Netflix, Spotify, Amazon and Uber</a>.</p><p>Java’s versatility makes it perfect for projects that make our day-to-day lives easier or enhanced, in a way. These include designing smart cities, electricity billing systems, ATM interfaces, currency converters, airline reservation systems, and various management systems, to name but a few.</p><blockquote><p>Putting Java in the limelight and discovering its lesser-known features is important as Java is, still, a very popular programming language. In the <a href="https://insights.stackoverflow.com/survey/2021" target="_blank" rel="nofollow">2021 Developer Survey</a>, it was revealed that over a third of developers (33.35%) utilized it, and it was named the fifth in the Programming, scripting, and markup languages category. And as far as the TIOBE Index is concerned, Java has been dubbed the third most popular programming language lately (as of October 2021). It was only beaten by Python and C.</p></blockquote><p>Along with Java itself, comes the Java Virtual Machine (JVM), used for running Java or Java byte code programs, with the number of users estimated in millions. Java operating system (JavaOS), Java compiler, Java Runtime Environment, and Java programs, in general, are also frequently used and talked about.</p><p><strong>Is Java’s platform independence an important feature for you? Which features are more important in your daily duties? What kind of projects do you use Java in your day-to-day work?</strong></p>

Why Java Is Platform Independent – Quick Guide | Codete Blog

Here's Why Java Is a Platform-Independent Language

<p>User experience and user engagement all rely on the perfect user interface, and here’s where <strong>Material vs Bootstrap</strong> opposition comes to play. And it's a major one, as both front-end frameworks are known as powerful tools used for web development in general, and creating responsive websites in particular.</p><p>They both have huge corporations standing behind them – Twitter in the case of Bootstrap (with the latter initially called Twitter Blueprint), and Google as far as Material Design is concerned. But they’ve both come a long way from what they were in the beginning, and currently are much more than just internal tools.&nbsp;</p><p>But what exactly can front-end developers gain by utilizing them? And what are the most significant constraints of doing so? Can we call any part of the Bootstrap vs Material UI opposition better?</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#lowdown">Bootstrap &amp; Material UI – the lowdown</a></p><p>2. <a href="#comparison">Bootstrap vs Material – which one is better?</a></p><p>3. <a href="#summary">Material Design vs Bootstrap boiled down</a></p><p>&nbsp;</p><div class="raw-html-embed"><section id="lowdown" style="height: 20px;"></section></div><h2>Bootstrap &amp; Material UI – the lowdown</h2><p>Before we get down to a Bootstrap vs Material comparison, we need to make sure what exactly both parts of this opposition are.&nbsp;</p><blockquote><p>Bootstrap is a front-end JS framework and can also be referred to as an HTML, CSS, or JavaScript library. It is known for being open-source and free, and its design templates can be used for things such as navigation, buttons, and typography, to name a few.</p></blockquote><p><a href="https://getbootstrap.com/" target="_blank">Bootstrap prides itself</a> for being „the world’s most popular front-end open-source toolkit, featuring Sass variables and mixins, responsive grid system, extensive pre-built components, and powerful JavaScript plugins”.</p><p>Also, GitHub users appreciate Bootstrap greatly, giving it as many as 153.000 stars – and thus a tenth place on the list of most starred projects (<a href="https://github.com/search?o=desc&amp;q=stars%3A%3E1&amp;s=stars&amp;type=Repositories" target="_blank">as of October 2021</a>). It enables creating cutting-edge web apps, and, apart from Twitter itself, is used by giants such as Dropbox, Bloomberg, and Airbnb.</p><blockquote><p>Material is one of the leading React UI libraries. It offers a big number of useful UI components – both foundational and advanced – that are additionally called self-supporting, simple, and declarative.</p></blockquote><p>It's advertised <a href="https://mui.com/" target="_blank">at its own website</a> as a „robust, customizable, and accessible library of foundational and advanced components, enabling you to build your own design system and develop React applications faster”.&nbsp;</p><p>Google’s Material Design, as its full name suggests, focuses on design building with the use of advanced, sophisticated theming features. It enables setting up design systems, design kits, and fully built templates as well as more flexible custom themes’ creation by front-end developers themselves. However, great design, Material’s hallmark, is to be paired with the innovative technical approach in the case of this popular library.</p><div class="raw-html-embed"><section id="comparison" style="height: 20px;"></section></div><h2>Bootstrap vs Material – which one is better?</h2><p>Keeping in mind that Bootstrap and Material are not identical toolkits, we may point out both similarities and differences between them. The latter concern, among others, possible applications and use cases so it’s essential to be aware of them before you decide to choose any of these. Moreover, Bootstrap is regarded as more versatile, being a CSS, HTML, and JavaScript framework while Material Design is a React-only library.</p><p>Bootstrap framework is valued for its <a href="https://codersera.com/blog/bootstrap-vs-material-ui-which-is-best-for-next-web-app/" target="_blank">impressive development speed</a> – due to its ready-to-use code blocks – and, for this reason, it is recommended for those front-end developers who need to deliver a web app or a website quickly. Material Design is, in general, worse on that end but using templates may increase the speed of development.</p><p>As for similarities, we may emphasize that both Bootstrap and Material UI offer good browser compatibility. Both frameworks have a 12-column grid system, enabling complete responsiveness. And both are regarded as reliable, appreciated, and frequently chosen by software developers.</p><p>However, as Material’s primal purpose was mobile devices, apps created with this design language look more modern, and its creators enjoy greater freedom when developing. It puts greater attention to things such as animation, pop-up, and sliders – elements that we won’t find within layouts created with Bootstrap, as the latter tends to be more elegant, stylish, and minimalistic – aligned with its information presenting purposes.</p><div class="raw-html-embed"><section id="summary" style="height: 20px;"></section></div><h2>Material Design vs Bootstrap boiled down</h2><p>What to choose, then, Material or Bootstrap? Well, it depends primarily on the project you are working on. Material Design framework offers an extensive library of powerful UI components that help developers build various types of user interfaces that are beautifully designed, ready-to-use and easily customized.</p><p>Material is a visual or design language with a grid system for layout creation in the very center. Thanks to it, advanced and more sophisticated effects such as vivid colors, <a href="https://en.wikipedia.org/wiki/Material_Design" target="_blank">lighting and shadows, padding, and responsive animations</a> are possible to achieve. In fact, it can be used to <a href="https://mui.com/" target="_blank">support building all types of user interfaces</a>.</p><p>Bootstrap, in turn, is a tool meant to simplify the process of developing <a href="https://en.wikipedia.org/wiki/Bootstrap_(front-end_framework)" target="_blank">informative web pages</a> and building easy, fast, responsive mobile-first sites, as well as mobile and desktop applications.</p><p>And for those who still can’t decide what’s better in the Material UI vs Bootstrap opposition, or want to make use of what’s best in both of them, there’s a nice combo called <a href="https://mdbootstrap.com/" target="_blank">MDBootstrap</a> or Material Design for Bootstrap v5 &amp; v4.</p><p><strong>And what toolkit do you prefer – Material Design or Bootstrap? What are your experiences with them? Can you spot other important use cases or features that are especially valuable in front-end developers’ work?</strong></p>

Material vs Bootstrap – Which One Is Better? | Codete Blog

Material vs Bootstrap. Which Frontend Framework Should You Use?

Managing Director at Codete. He is a Master of Law and has a Harvard Business School degree. A business leader with extensive experience in finance and team management. Specialist in startups and business development.

Grzegorz Śmiałek

CTO at Codete. In 2015, he received his Ph.D. from the Institute of Fundamental Technological Research of the Polish Academy of Sciences. His area of expertise is artificial intelligence.

Karol Przystalski

<p>Take a closer look at the financial services industry today, and you’ll see that it looked completely different 5 or 10 years ago. Due to the disruption caused by <internallink internallinkid="/blog/the-fintech-era-top-10-european-fintech-startups-to-watch-in-2019-and-growth-tips-for-the-future-market-leaders">fintech startups</internallink>, traditional banking and financial institutions had to embrace technology solutions – and most of the time, these solutions made use of data.&nbsp;</p><blockquote><p>Data is easily the most valuable resource for finance companies today. It allows them to learn more about customers to predict their future needs, identify fraud before it causes any damages, and automate their processes to achieve operational efficiency.&nbsp;</p></blockquote><p>But how exactly is <strong>data science applied in finance</strong>? Which solutions in the finance industry today make use of data science? Keep on reading this article to learn how data science is applied in finance and get inspired to develop a digital solution for your company.</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#intro"><u>What is data science?</u></a></li><li><a href="#applications"><u>Applications of the data science in finance</u></a></li><li><a href="#benefits"><u>Finance and data science – all the benefits</u></a></li></ol><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>What is data science?&nbsp;</h2><p>Every year, the financial services industry generates hundreds – if not thousands – of petabytes of data. Every single transaction leads to the creation of new data. The sector also embraced technologies like the Internet of Things, and these devices generate even more data.&nbsp;</p><p>The types of financial data are now more varied than ever. Apart from business intelligence tools, finance companies now need to log and analyze text-based data such as social media comments or reviews.</p><p><strong>Finding a way to build a data strategy across these dimensions is more challenging than ever. But unlocking the value from data leads to incredible success, as the fintech startups turned into unicorns illustrate.&nbsp;&nbsp;</strong></p><p>Since the data problem is both difficult and potentially valuable, a special profession for dealing with data emerged – it’s called data engineering. <strong>Data engineering</strong> is all about handling multiple sources of data and transforming data so that other specialists – for example, data scientists and machine learning experts – can use it.&nbsp;</p><p>And finally, we arrive at data science itself.</p><p><strong>Data science</strong> is a field that aims to extract meaning from complex and large-scale data sets. Data scientists allow businesses to focus on the insights that are valuable – for making accurate forecasts, minimizing risk factors related to financial decisions, and understanding customers better.</p><div class="raw-html-embed"><section id="applications" style="height: 20px;"></section></div><h2>Applications of data science in finance</h2><h3>1. Risk analytics</h3><p>Risk is a common component of running a business, but it’s especially prominent in the financial sector. Understanding the risk factor before making a decision is key – and this is where risk analytics comes in.&nbsp;</p><p>Using modern data science tools, banks can protect themselves against <internallink internallinkid="/blog/cybersecurity-in-banking-7-trends-for-2020"><strong>security threats</strong></internallink>. This is especially true if a lot of the organization’s risk is related to data that is unstructured. Analyzing it without the help of data science technologies is challenging and potentially subject to human error.&nbsp;</p><p>Moreover, data collected over time can provide incredible value to banks. Historical data offers <strong>insights into where losses were made</strong> and helps employees understand why that happened. The significance of a given loss and the frequency of its repetition can highlight problem areas that carry the biggest risk. That way, banks can avoid similar situations in the future. Once they identify a threat, they can rank it in line with their priority scheme and monitor its occurrence to take action whenever necessary.&nbsp;</p><p>Naturally, financial institutions are also in the business of <strong>analyzing the reliability of their customers</strong>. Machine learning algorithms are used here to browse through past transactions and general customer information to evaluate the relative risk of taking on a given customer or lending money to them.&nbsp;</p><p>Search models can <strong>instantly react</strong> to any new transactions or changes in customer information. Companies can develop a credit score for individuals based on what data scientists taught the algorithm about the specific type of customers and examples of historical risk.&nbsp;<br>&nbsp;</p><h3>2. Real-time data analytics</h3><p>Until quite recently, finance companies didn’t have access to real-time data. Essentially, all the analyzed data would already be out of date. Such data were processed in batches which meant that until a given update was completed, no analysis could take place. But drawing any insights from this data didn’t make sense. Finding meaning in figures that are days, weeks, months, or even years old is a bad idea.&nbsp;</p><p><strong>Today, banks can use real-time data analytics solutions that bring data science, machine learning, and business intelligence together to deliver the best experience using data that changes in real time.&nbsp;</strong></p><p>Businesses can respond to customer interactions instantly thanks to dynamic data pipelines, data streams, as well as a faster relay of data between the source and the analyst. As a result, <strong>real-time analytics</strong> helps to minimize the delay in identifying the value of customer interaction. Constantly updated credit scores and transactions are far more accurate and provide a better basis for decision-making.&nbsp;</p><p>&nbsp;</p><h3>3. Managing customer data</h3><p>Another application of data science in finance is about <strong>effective customer data management</strong>. Until recently, financial organizations processed customer data using machine learning capabilities in their business intelligence solutions. The rise of big data – and especially big volumes of unstructured data – made this method less effective.&nbsp;</p><p>Since there are more interactions taking place now than ever, there is even more valuable data that algorithms could be analyzing. And a lot of this data isn’t structured – coming from the Internet of Things devices or social media. Thankfully, data science comes to the rescue here thanks to the tools like data mining, natural language processing, and text analytics.&nbsp;</p><p>Such solutions lead to a significant upgrade in an organization’s analytical capabilities and generate deeper insights into customer behaviors in market trends.&nbsp;</p><h3><br>4. Consumer analytics</h3><p>Banks are now becoming customer-centric because they’re in tough competition with other finance companies and innovative fintech startups that make easy-of-access and customer-centricity their primary goals.&nbsp;</p><p>To provide <strong>personalized service</strong> to customers, a company needs to be able to process customer data quickly and efficiently. Real-time analytics work together with historical data trends to immediately analyze each customer’s transaction history and achieve goals such as:</p><ul><li>measuring the lifetime value of a consumer,</li><li>increasing up-selling or cross-sales opportunities,</li><li>eliminating below zero customers.</li></ul><h3><br>5. Personalized services for customers</h3><p>Banks and insurance companies use data science to maintain a certain level of security while also providing service to customers on a case-by-case basis.&nbsp;</p><blockquote><p><internallink internallinkid="/blog/hyper-personalization-in-banking-expert-guide">Personalization</internallink> is one of the strongest trends in the finance industry today, and data is its essential component. Becoming <strong>customer-centric</strong> means personalizing the experience for each individual customer. And it’s not just about the risk assessment. It’s about building a reputation and boosting the customer lifetime value.&nbsp;</p></blockquote><p>Everything – from phone conversations to customer reviews – can be analyzed to offer value to both the business and the customer. Understanding these interactions helps to create opportunities for valuable cross-sales by providing customers with products that match their exact requirements.&nbsp;</p><p>Software based on speech recognition or natural language processing can analyze these interactions and highlight opportunities to maximize sales, improve customer experience, and even lead teams in developing their future plans.&nbsp;</p><p>&nbsp;</p><h3>6. Customer service&nbsp;</h3><p>Together with personalized services comes the ability of data science to launch truly advanced customer service. Since the analysis of customer interactions can now happen in real time, customer service representatives can receive <strong>better recommendations</strong> from the system and handle the customer case as the conversation is happening.&nbsp;</p><p>For example, natural language processing solutions can show opportunities for giving actionable financial advice based on <internallink internallinkid="/blog/smart-conversational-banking-and-chatbots">what the customers are saying</internallink>. Digital solutions that analyze the customers purchasing patterns or pass transactions can suggest the next best actions to take to make a maximum impact during a sales interaction.&nbsp;</p><p>All of this enables the representative to cross- or up-sell effectively, all the while addressing the customer’s query. Data from every interaction can then be used as a foundation for similar interactions in the future. This means that the system is only going to become more and more effective with time.&nbsp;</p><p>&nbsp;</p><h3>7. Predictive analytics</h3><p>Predictive analytics solutions allow businesses to extrapolate from current data and <strong>predict what will </strong>happen in the future. This includes changing trends, customer behaviors, or risk.&nbsp;</p><p><strong>In the world of financial services, the ability to tell the future has massive consequences. Machine learning applications can learn from the past stock pricing and predict the stock market prices based on that to help customers make investment decisions or build smarter trading strategies.&nbsp;</strong></p><p>This is where machine learning algorithms come into play – engineers feed them pre-processed data so that the algorithms learn how to predict future events. The more data, the better the predictive model.&nbsp;</p><p>Moreover, the deep learning method can transform data on its own, without any pre-processing required from human data engineers.&nbsp;</p><p>&nbsp;</p><h3>8. Fraud detection</h3><p>The increase in financial transactions means more potential occasions for fraud. Identity theft or credit card schemes are now commonplace, so it’s essential that banks minimize the damage they cause by identifying issues as quickly as possible.&nbsp;</p><p>That’s why finance companies turn to data science tools that<strong> identify fraud</strong> early on. AI and machine learning algorithms can detect instances of credit card fraud far more accurately than other systems because they derive trends from a large quantity of data. They’re also able to react to suspicious activity in real time.&nbsp;</p><p>For example, if a large spend suddenly appears on a credit card owned by a customer who historically has behaved quite conservatively, the card can be canceled, and a notification sent out to the card owner. This protects the customer, bank, and the customer’s insurance company.&nbsp;</p><p>And in stock trading, machine learning solutions easily identify anomalies and <strong>instantly alert</strong> financial institutions to launch a rapid investigation.</p><div class="raw-html-embed"><section id="benefits" style="height: 20px;"></section></div><h2>Finance and data science - all the benefits</h2><p>There’s no denying that data science plays a critical role in the financial services industry by solving its core problems that arise from new customer behaviors and technology trends on the market.&nbsp;</p><p>Advanced algorithms, real-time data analytics, anomaly identification are just some of the many ways in which data science is disrupting the sector. If your company operates in the financial sector, it can use data for:</p><ul><li>smarter risk management,</li><li>improved profits and smaller losses,</li><li>automated and faster fraud detection,</li><li>personalization solutions to build a truly customer-centric business.</li></ul><p><strong>Are you looking for an expert team to help you implement any of the examples we shared above? Don't hesitate to </strong><a href="/estimation" target="_blank"><strong>get in touch with us</strong></a><strong>. We will help you understand the potential value of data science for your business.</strong></p>

Data Science in Finance - 8 Applications You Must Know | Codete Blog

Data Science in Finance - 8 Applications You Must Know

<p>Robotics brings together scientific and engineering disciplines to develop artificial embodied capabilities with the degree of autonomy.&nbsp;</p><blockquote><p>Any system that includes sensors, power supplies, control systems, manipulators, and software that performs the task of generating some action is a robot.&nbsp;</p></blockquote><p>Robotics is a rapidly evolving field that requires input from all kinds of disciplines - including software engineering for robot programming. So, what kind of programming languages are the best fit for those who would like to grow their careers in the robotics industry?</p><p>Read this article to see which technologies are the top choices of professionals working in the field today and which potential languages you should learn to launch a successful career in robotics.</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#intro"><u>Is a programming language for robotics different from other programming languages?</u></a></li><li><a href="#top8"><u>Top 8 programming languages for robotics</u></a></li><li><a href="#career"><u>Interested in a career in robotics programming?</u></a></li></ol><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>Is a programming language for robotics different from other programming languages?</h2><p>You might be wondering whether robotics makes use of languages that aren’t used in any other field. Luckily, that’s not the case. The most popular programming languages used in the field of robotics today are C, C++, Python, Java, C#, .NET, and others.</p><p>Apart from the Hardware Description Languages, they’re all used by software engineers across every industry. So, knowing them will come in handy if you’re transitioning to robotics from a software development career.</p><p>But whether you’re a <internallink internallinkid="/blog/how-to-become-a-senior-software-engineer-career-path-and-tips">senior</internallink> or a <internallink internallinkid="/blog/useful-coding-resources-for-beginner-programmers">newbie</internallink>, it pays to pick the languages that get you where you want to be in robotics and put your career on the right track.&nbsp;&nbsp;&nbsp;</p><div class="raw-html-embed"><section id="top8" style="height: 20px;"></section></div><h2>8 top programming languages for robotics&nbsp;</h2><h3>1. C/C++</h3><p>C and C++ are the two main programming languages used in robotics. They offer a great variety and number of tools, libraries, and functions that are useful in robotics. That’s why C and C++ are the top robotics languages today.</p><p>Most aspiring robotics engineers use them to program robots efficiently and ensure their high performance. If you’d like to build a career in the field of robotics, learning C and C++ is a great move. They’re also considered as very mature programming languages for robotics purposes because they enable easy interaction with low-level hardware that robots need.</p><p><strong>If the robotics device in question has limitations in memory, then standard C programming language is a better technology choice. If the use of the C language isn't dictated by this condition, robotics developers usually use C++.</strong></p><p>One of the greatest advantages of C++ is that the language controls the operating system’s API directly. This means that it doesn’t need any wrappers. This means that developers can use platform-specific libraries that work fast.&nbsp;</p><p>&nbsp;</p><h3>2. Python</h3><p><internallink internallinkid="/blog/python-advantages-and-disadvantages-every-developer-must-know">Python</internallink> is becoming more and more popular today due to its simple syntax, excellent documentation, and massive community. Since the language is easy to use, it requires less time for developers to learn it. And when you compare Python to other object-oriented programming languages such as C, C++, or Java, you’ll see that it saves you a lot of time when it comes to writing code.</p><p><strong>However, Python projects can get a little too complicated because it’s an interpreted language - spotting errors could become an issue. Still, Python is a high-level programming language that is extensively used for developing systems used in robotics applications.</strong></p><p>The language comes with a handful of useful features that make it a key player in the robotics scene. Some examples that show Python's strengths in robotics are Arduino or Raspberry Pi used for designing embedded systems.</p><p>Python is also surrounded by a rich ecosystem of libraries and packages that help to automate lots of things and save developers plenty of time because they don’t have to build functionalities from scratch. That can make a real difference in a robotics project.&nbsp;</p><p>&nbsp;</p><h3>3. Java</h3><p>Most universities that offer robotics courses include Java as a must-have programming language. Java is today used to build many high-level features that are required in robotics programming.</p><p>The Java Virtual Machine interprets instructions during the runtime of the code in a both fast and reliable manner. It’s a battle-tested and secure technology that offers special features to robotics for performing human-like tasks. For example, speech API or the Java Media framework are used to receive and process visual images.&nbsp;</p><p>&nbsp;</p><h3>4. Microsoft C#/.NET</h3><p>C# is a proprietary programming language provided by Microsoft. It’s often used in the Microsoft Robotics developer studio – and that’s why it deserves a mention here. Today, C# is considered one of the key languages for aspiring programmers in the robotics field. It gives you a solid foundation to branch out into different areas, including robotics.</p><p><strong>In general, C# and .NET are used at the port and socket level programming. That’s why they can also be used to implement neural network systems better than Java thanks to superior libraries for programming robots.&nbsp;</strong></p><p>Note: Microsoft also developed Visual Programming Language (VPL) for the Microsoft Robotics Studio - it's a handy visual and dataflow programming language.</p><p>&nbsp;</p><h3>5. MATLAB</h3><p>This high-performance language for technical computing integrates many things together programming, visualization, and computation. They are all served in an easy to use environment where developers can express problems and solutions in familiar mathematical notations.</p><p><strong>MATLAB is quite popular among beginner developers and often used for analyzing information and building control systems. It also comes in handy for modeling and simulation.</strong></p><p>MATLAB is an easy-to-use language that helps to eliminate implementation errors by allowing developers to identify problems already during the prototyping phase instead of later in the production (which is more costly).&nbsp;</p><p>&nbsp;</p><h3>6. Lisp&nbsp;</h3><p>One of the earliest programming languages, Lisp was originally developed for applied mathematical notation implemented in computer programs. However, you will find that many critical sections of the robot operating system are written in Lisp. That’s why it has also become a crucial language for the domain of <internallink internallinkid="/blog/8-surprising-real-life-artificial-intelligence-examples">artificial intelligence</internallink>.</p><p>Learning Lisp is a great start for stepping into the field of robotics. The language offers developers plenty of features such as automatic data storage management, dynamic typing, tree data structures, recursion, elevated order functions, conditionals, read-eval-print loops, self-hosting compilers, and many others.&nbsp;</p><p>&nbsp;</p><h3>7. Basic and Pascal</h3><p>Basic and Pascal are fundamental scripts that work across multiple industrial robot languages.</p><p>Basic and Pascal are currently outmoded by other trends and technologies but are still useful for beginners to understand the functionality and technicalities of robotics programming.&nbsp;</p><p>&nbsp;</p><h3>8. Hardware description languages (HDLs)</h3><p>This group of computer languages is used by developers to program electronic and digital logic circuits. Naturally, they’re extremely useful for anyone who wants to delve deep into the robotics industry. Hardware description languages are used to specify the gates and chips, as well as simulate the behaviors of the resulting chip specifications in a hardware simulator.</p><p><strong>Hardware description languages blur the distinction between software and hardware development thanks to design tools that allow developing real-time imaging hardware.</strong></p><p>Unlike the other languages that we mentioned above, HDLs require excellent knowledge of electronics since most of the operations are concurrent processor-based. These languages provide simple object orientation and garbage accumulation compared to other technologies.&nbsp;</p><div class="raw-html-embed"><section id="career" style="height: 20px;"></section></div><h2>Interested in a career in robotics programming?</h2><p>The field of robotics is rapidly expanding as more and more organizations invest in digital technologies to automate their processes, streamline their work, and develop new products for customers.</p><p>Industries ranging from manufacturing to retail are now interested in robotics, so the field is a great career choice for anyone. Mastering one or more of the best programming languages listed above is critical for entering this highly specialized and exciting industry.</p><p><strong>Do you know any of the languages listed above? Did they help you to launch your career in robotics? What other programming skills do developers need to become successful in robotics?&nbsp;</strong></p><p>Please share your thoughts in the comments to help beginners understand what it takes to succeed here and take the robotics field by storm.</p>

Top 8 Programming Languages for Robotics | Codete Blog

Top 8 Programming Languages for Robotics

Managing Director at Codete. Master of Law, a graduate of postgraduate studies at the University of Economics in Krakow. In his daily work, he masters the combination of business strategy and technology.

Artur Olechowski

<p>The <internallink internallinkid="/blog/digital-transformation-in-retail">online retail</internallink> space is growing faster than ever, and the COVID-19 pandemic has only accelerated its growth. Judging by consumer behaviors today, it shouldn't come as a surprise that in the future, the majority of purchases will be made using mobile devices.</p><p><strong>Recent statistics show that in 2021, mobile commerce sales represented </strong><a href="https://www.statista.com/statistics/806336/mobile-retail-commerce-share-worldwide/" target="_blank" rel="nofollow"><strong><u>72.9%</u></strong></a><strong> of e-commerce sales worldwide.</strong></p><p>That's why so many retailers have already moved to mobile platforms, driven by the vision of increasing their revenue, reaching new target audiences, and expanding their business operations. Almost everyone has a smartphone these days and uses wireless handheld devices for communication but also entertainment, education, and shopping.&nbsp;</p><p>So many things can be done with just one click of a button!</p><p>Applications like Google Pay and Apple Pay have revolutionized the way we make payments and originated the use of mobile phones as digital wallets, locking in all the important functionalities people need when on the go.&nbsp;</p><p>But what exactly is <strong>m-commerce</strong>? And what kind of advantages does it offer to companies? Keep on reading this article to see what m-commerce is, what its most important types are, and what are its critical benefits that will make a massive impact on retail in the near future.&nbsp;</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#intro"><u>What is m-commerce?</u></a></li><li><a href="#types"><u>Types of mobile commerce</u></a></li><li><a href="#pros-and-cons"><u>How m-commerce works + advantages &amp; disadvantages</u></a></li><li><a href="#future"><u>The future of m-commerce</u></a></li></ol><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>What is m-commerce?&nbsp;</h2><p>M-commerce is short for mobile commerce, a type of online commerce that carries out digital transactions right inside mobile devices such as smartphones or tablets. There is no need for people to come into physical contact for sending or receiving money. In other words, mobile commerce is about buying and selling goods and services using mobile devices.&nbsp;</p><blockquote><p>M-commerce is a form of e-commerce, but instead of enabling services through online shopping platforms on desktop computers, it all happens on mobile devices.&nbsp;</p></blockquote><p>Interestingly, the term "mobile commerce" was originally coined <a href="https://en.wikipedia.org/wiki/Mobile_commerce" target="_blank" rel="nofollow"><u>in 1997</u></a> during the launch of the Global Mobile Commerce Forum. Back then, it meant the delivery of e-commerce capabilities directly into the consumer's hand through wireless technology. It's hard to believe that the idea was born such a long time ago, and we only see it flourish right now.</p><p>Here are a few examples of m-commerce that will instantly show you the extent to which it fills our everyday lives:</p><ul><li>mobile banking,</li><li>virtual marketplace applications (like the Amazon or Alibaba mobile apps),</li><li>digital wallets such as Apple Pay, Android Pay, Google Pay,</li><li>mobile ticketing.</li></ul><div class="raw-html-embed"><section id="types" style="height: 20px;"></section></div><h2>Types of mobile commerce</h2><p>As you can see, m-commerce is a rather broad category that encompasses anything from mobile shopping and mobile payments to mobile banking services.&nbsp;</p><p>Let's take a closer look at the types of m-commerce available to businesses today:</p><h3>1. Mobile shopping</h3><p>Mobile shopping brings the ease of shopping to the customer right on their mobile device. The interesting part is that m-commerce can take on many different forms here. Customers can buy products on mobile devices inside the web browser, over a web application, or using a native mobile application.</p><h3>2. Mobile banking</h3><p>As traditional financial services companies experience more competition from <internallink internallinkid="/blog/the-fintech-era-top-10-european-fintech-startups-to-watch-in-2019-and-growth-tips-for-the-future-market-leaders">fintech startups</internallink> and the finance industry is disrupted by innovative technologies, the need for mobile banking is on the rise. Developing a customer-centric experience has become the primary goal of many financial services firms. That's why they turn to mobile banking - the idea here is delivering banking products and services to customers via secure mobile applications.&nbsp;</p><h3>3. Mobile payments</h3><p>This subcategory of m-commerce is closely related to the other two because it enables users to purchase products using a mobile device and removes the friction from completing the transaction. Good examples of mobile payments are digital wallets - for example, Apple Pay or Google Pay. They allow customers to buy products without having to swipe a card, pay with cash, or even type in the details of their credit card into the application.&nbsp;</p><p>An interesting development in this category is mobile person-to-person personal payments realized by applications like Venmo. They allow sending money from one person to another quickly - all that you need is someone's phone number or bank account, and the transaction can proceed directly.&nbsp;</p><p>Mobile payments now include the following innovations:</p><ul><li>mobile wallets (also referred to as digital wallets)</li><li>contactless mobile payments</li><li>closed-loop mobile payments</li><li>money transfers</li><li>carrier payments</li><li>mobile point-of-sale (POS)</li></ul><div class="raw-html-embed"><section id="pros-and-cons" style="height: 20px;"></section></div><h2>How m-commerce works + advantages &amp; disadvantages</h2><p>M-commerce enables mobile devices to become connected to a wireless network that is in turn used to realize online product purchases. Depending on the application's purpose, you'll be looking at different software architectures, and UX design – these two elements have a massive impact on how a given application works.</p><p>Still, teams in charge of building m-commerce applications should take into account important KPIs that feed into mobile analytics solutions like the total mobile traffic, average order value, and value of orders over time. It's important to track the mobile app's add-to-cart activities to examine how quickly visitors are becoming customers and how many of them become paying customers, not just people who browse for items.&nbsp;</p><p>M-commerce products usually operate through some form of peer-to-peer sharing. For example, a bank can pair a mobile device with the customer's card information so that users can simply touch their phone to a payment terminal in order to pay for the product. This use of mobile devices is made possible through the use of Near Field Communication (NFC).&nbsp;</p><p>&nbsp;</p><h3>Advantages of m-commerce</h3><h4>1. Improved customer retention</h4><p>By making content available to customers on the go, brands can enjoy better customer retention rates and become more accessible to people. Providing users with a means to easily purchase products on their mobile phones is a smart move because it expands the range of contexts where such purchases can take place.&nbsp;</p><h4>2. Larger target market</h4><p>By investing in m-commerce, you can reach more customers - especially among younger audiences who spend a lot of their time on their phones. M-commerce allows customers to discover products easily. Smart businesses use mobile commerce applications in line with popular social media applications like Facebook or Instagram to engage new customer segments and carry out successful remarketing.&nbsp;</p><h4>3. Better user experience</h4><p>Mobile commerce applications offer fast and convenient access to products. These applications are often interactive and provide users with exclusive deals or promotions while these customers are shopping inside the brand's brick-and-mortar stores. As a result, they deliver a superior user experience to other types of m-commerce.&nbsp;</p><h4>4. New mobile marketing channels</h4><p>A mobile application is also a brand-new marketing channel where companies can:&nbsp;</p><ul><li>share information about their products,</li><li>allow users to search for features,</li><li>create a newsfeed,</li><li>deliver special sales and promotions via push notifications to become closer to their target audience.</li></ul><h4>5. Personalized notifications and location tracking</h4><p>Since mobile devices are carried by users everywhere they go, location tracking can be credibly helpful if you'd like to assist them while they're navigating the store. You can also understand where users are to send them a location-based push notification featuring personalized discounts – all to increase your sales volume. This is the first step to developing a truly omnichannel buying experience that drives more conversions home.</p><p>That said, m-commerce comes with several key challenges that you should be aware of before embarking on the m-commerce journey.</p><p>&nbsp;</p><h3>Disadvantages of mobile commerce</h3><h4>1. High cost</h4><p>The technology required for setting up an m-commerce application is quite expensive at the moment. Such a capital investment is still impossible for many businesses that would like to expand their operations to mobile commerce.&nbsp;</p><h4>2. Access to the internet is critical</h4><p>If you're operating in a country where the network signal isn't great, and providers are incapable of offering good connection speed, your application might not perform as well and reach as many people as you would like to. You need a connection strong enough for data transfer, especially if you plan to include video content or images in your application.&nbsp;</p><h4>3. Security demands</h4><p>Another important matter is security. It's essential that applications are kept safe. This goes especially for mobile banking applications where one data leak or any other security risk might mean a loss of reputation for the entire company.&nbsp;</p><h4>4. Excellent design is a must-have</h4><p>A poorly designed app with a bad user experience might reduce the number of purchases and lead to customer dissatisfaction. Problems like lags or content taking too long to load are all relevant here because they contribute to the user experience.&nbsp;</p><h4>5. Accessibility matters</h4><p>Mobile payments are present in most countries, but they are still not available across all the locations in the world. Take this into account and consider whether or not your target audience is likely to use their smartphones that way – whether it's to make purchases or use mobile systems for payments. Do this before investing in a costly mobile application.&nbsp;</p><p>&nbsp;</p><h2>The future of m-commerce</h2><p>M-commerce is a rapidly expanding field as plenty of companies are now investing in building their own mobile applications. This would be happening anyway, but the COVID-19 pandemic accelerated this process by causing some pretty dramatic changes in consumer behaviors.&nbsp;</p><blockquote><p>One of the most significant future trends of m-commerce is its sheer market share and growth. E-commerce sales are expected to rise to over <a href="https://www.statista.com/statistics/272391/us-retail-e-commerce-sales-forecast/" target="_blank" rel="nofollow"><u>$735 billion by 2022</u></a> – and a huge chunk of that number will be sales coming from mobile devices like smartphones and tablets.&nbsp;</p></blockquote><p>We hope that this article helps you understand what m-commerce is, how it works, and how you could harness its potential for your business.&nbsp;</p><p>At Codete, we have realized a number of mobile commerce projects for clients across different industries and know what it takes to build a successful application.&nbsp;</p><p><strong>If you're looking for some more advice or want to hire an experienced team with an excellent track record, </strong><a href="/estimation" target="_blank"><strong>get in touch with us</strong></a><strong>. We can help you build a mobile commerce experience that realizes all the potential benefits of this fantastic technology.</strong></p>

What Is M-Commerce? Definition & Examples | Codete Blog

What Is M-Commerce? Definition and 3 Examples

Engineer passionate about building stuff displayed in the browser window but not only. Almost like Iron Man in software development, so maybe Software Man?

Szymon Oleszek

<p>What would the IT project look like if we wrote everything from scratch? Well… most probably, quite OK if the app is easy or you have a lot of time to spend on designing it. But when it comes to delivering things fast and with good quality in mind, additional tooling is where you should look for help.&nbsp;</p><p>It’s widely known that bigger projects frequently use things that already exist and you don’t need to reinvent the wheel. Every programming language ecosystem has its own source of these ready-to-use parts. Some of them include Maven, RubyGems, or the title NPM. But can we place NPX on this list? And what is the relationship between the NPX / NPM couple? Let's see.</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#intro">NPM in a nutshell</a></li><li><a href="#npx">What is NPX? Is it a better version of NPM?</a></li><li><a href="#differences">NPM vs NPX – 3 main differences</a></li><li><a href="#choosing">NPX or NPM – which one to choose?</a></li></ol><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>1. NPM in a nutshell</h2><p><strong>NPM</strong> stands for <strong>Node Package Manager</strong> and is considered to be the largest software registry. However, the registry is only one part out of three NPM consists of. NPM has its own web app for viewing and managing pieces of software that are stored in the registry - which is nothing else than a public database of JavaScript software and related metainformation.&nbsp;</p><p>Those pieces of software are commonly named and called <i>packages</i>. In addition to this, NPM gives you the possibility to create user accounts and cooperate with others to develop public or private packages. Last, but not least, part of NPM is the Command Line Interface (CLI). NPM’s CLI gives you plenty of commands, and each of them is very well described. Oftentimes, the documentation is enriched with short but very descriptive information.</p><p>Examples of NPM commands are as follows:</p><ul><li>“<code>npm init</code>” - a command to initialize a new npm package; after the invocation, the file named package.json appears in the directory in which this command was invoked</li><li>“<code>npm install &lt;package-name&gt;</code>” - another commonly used command that installs a package and any packages that it depends on. All of those packages can be found in the node_modules folder that should appear following the installation of the first package.</li><li>“<code>npx &lt;package-name&gt;</code>” - npx… it’s not a mistake - npx is another command of NPM CLI that allows us to run packages without downloading.</li></ul><p>To get to know the rest of the NPM commands and see how powerful NPM is - see the documentation.</p><p>What’s also important, is that the prerequisite to use NPM CLI in a given terminal is to have Node installed on the machine. And NPM as a Node Package Manager comes with this installation.</p><div class="raw-html-embed"><section id="npx" style="height: 20px;"></section></div><h2>2. What is NPX? Is it a better version of NPM?</h2><p>We already know the answer to the second question from the last example of NPM commands. We cannot think of it as being the equivalent of NPM because it is one of its commands. However, this command is a bit different than others. It comes with NPM if we have a version of NPM that is 5.2 or higher.</p><p>The <strong>NPX </strong>stands for <strong>Node Package Execute</strong>. It can also be called the npm package runner that can execute packages that you want from the npm registry without installing it locally.</p><p>A very good and descriptive example of how NPX is used and how it works is a simple project that consists of an index.html file without any <code>package.json</code> and <code>node_modules</code>. To run this project to preview the result, you can use the package called “serve” that is published on the npm registry.&nbsp;</p><p>To do this, you have two ways - the first one is to initialize the new package (<code>npm init</code>), then install the “<code>serve</code>” package locally (<code>npm install serve</code>), and next add a new npm script in the <code>package.json</code> file that can invoke the “<code>serve</code>” script. The second one is when NPX comes to play and you don’t need to invoke all of these commands except for the “<code>npx serve</code>” one.&nbsp;</p><p>This simple example shows that we don’t need to install packages on our machine to use them. We can just run them by invoking “<code>npx &lt;package_name&gt;</code>” and we don’t need to worry about initializing or installing something additional.</p><div class="raw-html-embed"><section id="differences" style="height: 20px;"></section></div><h2>3. NPM vs NPX – 3 main differences</h2><p>Now that we have definitions of both tools, let’s compare them in some crucial aspects. What is difference between NPX and NPM?</p><p>&nbsp;</p><h3>Difference 1: Running packages as developer tools/dependencies (e.g. ESLint, Serve, Nodemon, etc.)</h3><p><strong>[NPM]</strong> NPM itself is not a package runner. If you want to run a package by npm command you need to specify this package in package.json or install it globally and then run it.</p><p><strong>[NPX]</strong> NPX by definition is a package runner so you can simply use it to run any executable package from the NPM registry but not only from there as NPX gives you the possibility to run gists from Github, too.</p><h3>&nbsp;</h3><h3>Difference 2: Packages as dependencies of the web/server project</h3><p><strong>[NPM]</strong> allows us to install packages locally and store them in <code>node_modules</code> - which, with the additional help of other tools, makes packages visible and accessible in the project.</p><p><strong>[NPX]</strong> NPX is not a tool for installing packages. It is not the purpose of NPX.</p><h3>&nbsp;</h3><h3>Difference 3: Testing different versions of executable packages</h3><p><strong>[NPM]</strong> Testing different versions of packages by installing them first and then executing them is possible but, in comparison to NPX, can be uncomfortable and ineffective in the long run.</p><p><strong>[NPX]</strong> NPX is a good tool to test different versions of packages. We don’t need to worry about installing different versions, again and again, we can just simply run the “<code>npx &lt;package-name&gt;</code>” and specify its version.</p><div class="raw-html-embed"><section id="choosing" style="height: 20px;"></section></div><h2>4. NPX or NPM – which one to choose</h2><p>If you still have doubts concerning the NPM NPX use, the answer is quite simple: use both, as both are handy and necessary. NPX is a very handy add-on to NPM, and there are some things we can do by using NPX, and some things we can do by using NPM. Good example that confirms this statement is the setup of the ReactJS project through the create-react-app package. We can simply run the “<code>npx create-react-app &lt;name-of-app&gt;</code>” command which generates the whole structure of the project with the required dependencies. In the case of most of the projects that need additional packages, the latter may be installed by the “<code>npm install &lt;package-name&gt;</code>” command.</p><p>With that being said, we’ve got knowledge about what NPM and NPX are and why, in real life, we use and need both of them. We’ve learned the common use cases of both of them, as well as how the basic commands look like. NPM is a very big and complex tool. It comes with plenty of different packages that have millions of downloads but certainly not every one is worth installing.</p><p><strong>And what are your preferences in the NPX vs NPM competition? Do you have experience with utilizing any of these tools? To you, which one is more valuable and useful?</strong></p>

NPX vs NPM – Which One to Choose? Comparison | Codete Blog

NPX vs NPM – 3 Key Differences

<h2>We partnered with a well-known tech university from the United States to build a fully automated, NLP-powered social media monitoring tool for sentiment analysis.</h2><p>Codete's researchers are involved in both internal and external projects. We cooperate with leading technology universities in the world in the area of Research &amp; Development (R&amp;D). Our work is mostly focused on (but not limited to) data science, image and video processing, as well as NLP.&nbsp;</p><p>In this project, we used NLP to create a tool for monitoring social media content and analyzing sentiment in the posts.</p><figure class="image" height="631" width="1201"><img src="https://storage.googleapis.com/codete-live-strapi-uploads/codete_case_study_dmt_1_e8c5f205f8/codete_case_study_dmt_1_e8c5f205f8.png"></figure><h3>&nbsp;</h3><h3>Challenge: Real-time sentiment analysis with machine learning</h3><p>The growth of social media usage changed the world of marketing. It has never been easier to deliver content than it is now. Any information can spread across the globe in less than a second, so it is critical to recognize what is happening with your product or brand as soon as possible.&nbsp;</p><p>It is especially important if something goes wrong or if you want to see how other people perceive what you do. That is why we believe that having continuous and fully automated social media monitoring tool is a must-have for all businesses, and sentiment is one of the most important factors to monitor.</p><p>&nbsp;</p><h3>Solution: Custom NLP solution for Twitter</h3><p>Our partner's CoreNLP is a cutting-edge NLP library that we intended to use for our content monitoring tool, but its accuracy was only about 50%, which fell short of our expectations. The tool was intended to work with longer, usually grammatically correct texts, but because Twitter limits message length and the platform's users don't care that much about linguistic correctness, the library's ability to work properly with the texts we had was unsatisfactory.&nbsp;</p><p>We created our own solution by combining the TFIDF vectorization method, PCA, and Random Forest classifiers. We collected publicly available datasets of tweets labeled with their sentiment for the training phase. As a result, our method achieved over than 75% accuracy.</p><p>&nbsp;</p><h3>Tech stack</h3><figure class="image" height="81" width="274"><img src="https://storage.googleapis.com/codete-live-strapi-uploads/codete_case_study_dmt_tech_stack_84b06c3c44/codete_case_study_dmt_tech_stack_84b06c3c44.png"></figure><ul><li>Python</li><li>Scikit-learn</li></ul><p>&nbsp;</p>

Case Study: Content Monitoring Tool | Codete Blog

Case Study: Content Monitoring Tool

Software Developer. Passionate about creating readable and testable code. Python enthusiast since version 2.0.

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