Plenty of development life cycles are involved in a software project, so selecting the correct one becomes difficult. Software Development Models should be selected wisely by looking at the budget, team size, project criticality, and criticality of the product. Choosing the suitable model will improve the efficiency of your IT projects and manage risks associated with the software development lifecycle.

There are many embedded systems out there, but only a few static code analysis tools that realistically support embedded software developers. The recent acquisition of Micro Focus by OpenText, including the Fortify Static Code Analyzer, reignites the question of which static code analysis tool is best for your embedded software project. Between Fortify and Klocwork, our experts have the answer.

Big Data started as a replacement for data warehouses. The Big Data vendors are loath to mention this fact today. But if you were around in the early days of Big Data, one of the central topics discussed was — if you have Big Data do you need a data warehouse? From a marketing standpoint, Big Data was sold as a replacement for a data warehouse. With Big Data, you were free from all that messy stuff that data warehouse architects were doing.

The difference between consuming data and actioning it often comes down to one thing: effective data visualization. Case in point? The John Snow’s famous cholera map. In 1854, John Snow (no, not that one) mapped cholera cases during an outbreak in London. Snow’s simple map uncovered a brand new pattern in the data—the cases all clustered around a shared water pump.

We’ve all heard about the significant WhatsApp breakdowns that have happened in the recent past, during which the app was unavailable for the public for an hour. However, from a technical standpoint, WhatsApp returned in less than an hour. What would have enabled the engineers at WhatsApp to quickly restore the services? Technically speaking, the team experienced an extremely stressful production failure because of this.

One major reason for digging into API and product analytics is to be able to easily identify trends in the data. Of course, trends can be very tough to see when looking at something like raw API call logs but can be much easier when looking at a chart aimed at easily allowing you to visualize trends. Enter the Time Series chart.

Developing high-quality apps involves pressure to make tradeoffs on speed, quality, and features to meet deadlines for release. This tension between speed and quality comes to a head with QA: you need a functional product but can’t afford weeks of turnaround time. You can’t skip QA: the true cost of software bugs – the direct cost of mitigating the defects and the indirect cost of decreased consumer trust – is extraordinary.

Conceptually, a paradigm is a system of concepts and practices that reflect the current state of our understanding of the field. In general, a programming paradigm refers to a style, way, or classification of programming. Programming languages are used in order to solve problems. A paradigm's difficulty varies according to the language. Paradigms can be used in several programming languages, but a strategy or methodology must be followed.

Developing applications in Linx follows common programming paradigms. This means that it will use variables, loops and if statements in a similar fashion to a traditional programming language. With this in mind, a recent update (6.4.1) introduced the Return function. The Return function is the new standard for returning values to the result of a function or to exit a function at any point. This post will go over what the Return function does and how it can be used.

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.