A selection of the top articles and videos from the last week on SystemsDigest.com. Don't forget to check back regularly for daily updates from around the globe.
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JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages (C, C++, JavaScript, and so on). These properties make JSON an ideal data-interchange language. If you're working with Node.js, chances are you'll need to read and write data to a JSON file at some point. Imagine you have a purchase_history.json file that contains a record of customer purchase order information.
Data modeling is the process of organizing your data into a structure, to make it more accessible and useful. Essentially, you’re deciding how the data will move in and out of your database, and mapping the data so that it remains clean and consistent. ThoughtSpot can take advantage of many kinds of data models, as well as modeling languages. Since you know your data best, it’s usually a good idea to spend some time customizing the modeling settings. This will make the data more intuitive to search for your end users. There are 3 common types of data models: relational, hierarchical, and network database. In this article, we’ll break down each one and explore the pros and cons, so you’ll know when you should use each type to model your data.
Larval is one of the most popular PHP frameworks, created especially to help developers quickly build web applications. According to builtwith.com, more than 27.5 million websites use a PHP framework, making up 14% of worldwide websites. However, you should always adhere to the following Laravel best practices to make Laravel development a breeze and reap maximum benefits.
Organizations worldwide put their best foot forward to create a centralized database where information is gathered, stored, and managed. Their data engineers transform difficult-to-decipher datasets into data pipelines that can be used by data scientists, analysts, and consumers. However, the new data mesh concept championed by Zhamak Dehghani, the director of technology for IT consultancy firm ThoughtWorks, allows domain teams to conduct cross-domain data analysis independently. This approach is focused on the decentralization of data. Before delving into its architecture, let us first understand what data mesh is and how it functions.
WSO2 recently announced the release of their Private CIAM Cloud service, and it made me think about the changing role of personal identity versus business entity in today’s complex distributed software environments. The CIAM space has evolved far beyond the traditional end user’s need for identity and access to applications in a B2C (business to customer) scenario. The ‘C’ in CIAM doesn’t just stand for ‘customer’ anymore, it is now an essential catalyst for businesses to safely work with any constituents: end customers, businesses (B2B), employees (B2E), citizens, and even communications among API-enabled services.
Job scheduling is the process of starting a job, task, or function at a specific time or when specific events take place. Cron, the time-based job scheduler used in Unix-like systems, is the basis for the majority of job schedulers. Numerous job schedulers are available for the Node.js runtime environment. While some of these schedulers operate in both the browser and Node, others exclusively in Node. Choosing the best scheduler for your use case can be challenging and time-consuming because each of these schedulers has its own characteristics.
Do you have a Node.js project that you want to put into production but don't know how? In this tutorial, you'll learn how to deploy a Node.js and MongoDB application to Heroku. Before we get started, let's take a very quick look at Heroku and MongoDB.
Today organizations are looking for better solutions to guarantee that their data and information are kept safe and structured. Using a data lake contributes to the creation of a centralized infrastructure for location management and enables any firm to manage, store, analyze, and efficiently categorize its data. Organizations find it extremely difficult to deal with data because the information is kept in silos and in multiple formats. Concepts like data lake have emerged in response to the increased demand for agile data analytics from massive data volumes.
Phoenix LiveView 0.18 just shipped, with lots of new goodies to make developing LiveView an even better experience. In this post, I'll take you through a lesser-known new feature - LiveView's new special HTML attributes - and show you how to write cleaner HTML with :if, :for, and :let. When we're done, you'll have an eloquent, ergonomic, and dynamic function component you can use to render a list anywhere in your LiveView app. Let's dive in!
In any application, testing is crucial, as it verifies that everything is working as expected and that what we are going to deliver to the end user is what was described in the project plan. Typically, it allows developers to inspect whether their app meets functional, performance, and UI specifications. Web applications can be tested using a variety of methods and types. These testing methods have already been combined into reusable libraries by many open-source developers. Similar to JavaScript's React ecosystem which abstracts the view layer of applications, React is a framework that abstracts the view layer of an application.
Self service analytics (also called self-service business intelligence, or self-service BI) is a term commonly used among analytics vendors and organizations adopting BI, often in the context of being the next big thing in driving more people to use data to find insights. But what is self service analytics? How does self service analytics work? And why does self service analytics matter? In this blog, we explain the meaning of ‘self service’, defined in the context of business intelligence solutions, to help you understand its differences, purpose, and benefits.
Companies around the world are developing new frameworks for data analysis and the management of cloud-scale data, often based on emerging technologies such as machine learning. While data should be a competitive advantage for a company, without the ability to address complex data at scale most will struggle to bridge the gap and get value from their expensive data infrastructure and assets.
Gherkin language is a simple yet effective syntax for describing the specifics of your User Stories. Although Gherkin's Given-When-Then structure has been available for over a decade, many groups still don't make use of it.
Legacy applications pose multiple problems for data-driven organizations like yours. Outdated software might no longer receive support and maintenance from its vendor or might not integrate with modern technologies like cloud computing. Still, these applications are essential for day-to-day business tasks, and replacing them could impede productivity and profitability. Upgrading legacy applications— instead of substituting them—can save costs and increase flexibility, scalability, and security. There are various ways to upgrade a legacy application. The approach you take to modernization depends on your budget and business initiatives.
There is no denying the fact that React Native is the future of developing hybrid apps. It offers scalability, flexibility, speed, agility, cost-efficiency and excellent performance. No wonder so many successful companies rely on React Native for building their applications. After all, in the age of the Internet, every business needs a high-performing app that squarely satisfies customer needs. React Native tries to provide everything that is needed to develop a high performing application. But, there are occasions when you may feel the need to optimize your app. You may opt for professional React Native Development Services for improving the performance of your app. Or, you can learn and implement best practices on your own.
Laravel provides a file system abstraction that includes simple drivers for working with local filesystems, SFTP, and Amazon S3. This article teaches how to use Amazon S3 in Laravel.
Codeless automation testing is performing automation tests without having to write any code. It can be instrumental in executing continuous testing as most automation scripts fail due to the deficiency of proper coding standards. It will also enable us to concentrate more on test creation and analysis instead of fearing getting the code to work, possessing it, and scaling it when required. So, if we are relatively codeless in automation testing, we will find this blog helpful. By comparing it with Selenium testing, we will highlight the advantages of codeless automation testing. So, let us get started.
Responsive and robust web apps have become an unsaid necessity for modern businesses. For this, the use of the traditional tech stack of JS, HTML, and CSS in the website frontend is not enough. Instead, developers must shift to more modern and robust development alternatives to create web applications that answer complex business needs while guaranteeing effortless performance. A majority of developers are using React with Bootstrap to achieve this goal in their web development projects. If you’re wondering how you can craft robust and responsive web apps, this blog is just the right place to begin.
Does your Ecommerce business team understand the customer journey? By tracking the history of individual customer behavior and customer interactions across different channels, your organization can better understand what motivates your audience — and cater to them with the right marketing campaigns.
The Python ValueError is an exception that occurs when a function receives an argument of the correct data type but an inappropriate value. This error usually occurs in mathematical operations that require a certain kind of value.
Testing for quality assurance (QA) is a fundamental and essential component of software development. Not only is it necessary to ensure that all the critical elements of software projects are in place to be delivered on schedule, but it also contributes to raising the project’s overall quality. This is why QA candidates need to have a strong understanding of various concepts and be able to answer tricky questions.
Starting a company that works in any field is an exciting journey. We start with probably ten people and almost no user base in the initial days. But if our services are user-centric and our product solves a good problem, we will grow in both these dimensions. When our user base grows, and we expand our services, we generally ask our engineers to make our systems even better for them. For example, search should be within milliseconds even if we have millions of products (considering the eCommerce domain). We make our designs better, algorithms better, architecture better, and much more. However, in this process of making our product better, we are constantly expanding our team. Soon we realize that our team has grown to a level where manual management is no longer possible. Hence, we turn towards products like SAP that work well as long as SAP testing has been efficient and of top-quality.
Artificial Intelligence (AI) is quite powerful and is constantly evolving and currently knows no bounds. It is focused on outperforming its limits using the power of Machine Learning (ML). AI is empowering computers to do things that human beings are unable to do efficiently and effectively and machine learning is aiding the computers to do so by breaking the rules of traditional programming. We are aware that AI/ML has been driving an era of automation that holds important benefits for global industries like increased productivity, and time to market as companies have started relying on technologies to optimize their internal business operations.
Many businesses are shifting their focus toward mobile app development as the demand for mobile apps increases. Innovative mobile apps are being developed with the help of new technologies, platforms, and frameworks. A new trend in mobile development is cross-platform app development, which allows developers to create apps for multiple platforms, such as Android, iOS, and Windows. By choosing React Native for your multi-platform mobile app development, you can be confident you made the right choice. This is because JavaScript is integrated into the native language of React Native.
So much relies on data these days that it might be safe to say that most companies can’t thrive without it. Yet, gathering data is just the start — using it to make better company decisions or improve business processes is the end goal. Unfortunately, collecting large quantities of data for your business might seem futile if that data remains cut off from other systems. As such, it has become vital for developers and decision-makers to unify data for practical use. You can consistently compile relevant information from multiple systems through the power of data integration.
The data landscape is exploding with tools. As data professionals we have at our fingertips specialized tools for anything: from specialized databases (graph, geo, you name it) to tools for SQL-driven transformations (looking at you, dbt). Yet, a lot of data work is about provisioning, selecting, administering, and just maintaining those tools. Which is just a pain. As Pavel Dolezal, CEO and co-founder of Keboola said: The answer is in how the Modern Data Architecture is built.
Data integration is the data engineering process of combining data across all the different sources in a company (CRM, SaaS apps like Salesforce, APIs, …) into a single unified view. The data integration process includes data extraction, data cleansing, data ingestion, data validation, modeling, and exposing ready-to-be-consumed data sets to other users and applications for business intelligence or data-driven activities. The right data integration tool helps you speed up the data lifecycle and reach the point where data drives business results faster.
