While cloud providers and data analytics firms are proliferating across markets and landscapes, what distinguishes one from another? How can you know which one holds the keys to your agency’s digital transformation? The reality is that no matter how slick the advertising, how pervasive the presence across conferences and webcasts, or how high the C-suite’s former government offices … it’s the offerings that matter most.

Many enterprise data science teams are using Cloudera’s machine learning platform for model exploration and training, including the creation of deep learning models using Tensorflow, PyTorch, and more. However, training a deep learning model is often a time-consuming process, thus GPU and distributed model training approaches are employed to accelerate the training speed.

We all know visualization alone is not enough in the world of modern BI. And, when Qlik Sense was introduced, we focused on building a world-class platform, driven by our associative engine, open APIs and modern architecture. Our vision was to drive all the major analytics use cases, and support a lightning fast pace of innovation for the next decade and beyond.

In today’s enterprise computing landscape, multi-cloud organizations are quickly becoming the norm rather than the exception. By leveraging an API-first strategy with a microservice-based architecture, companies can achieve significant speed to market across multiple clouds. In order to achieve this, container orchestration and a well-designed CI/CD strategy are essential components in this journey.

In today’s post, we’ll learn about Mnesia, see when you would use such a tool, and take a look at some of the pros and cons of using it. After covering the fundamentals of Mnesia, we’ll dive right into a sample application where we’ll build an Elixir application that uses Mnesia as its database. Let’s jump right in!

Time series data and real-time data acquisition is growing at a 50% faster rate than static, latent, or historical data. In some ways, it has become more important than any other type of data, as it provides real-time decision making, enables autonomous decisions at the edge, and allows for more complex Machine Learning (ML) applications. Time series data and real-time data acquisition dominate industrial use cases, as it is ubiquitous with the manufacturing process.

Software testing is the process of finding bugs or discrepancies in a software. It is a process put in place to check that an application, set to be released in the market for users, has a minimum number of errors. Even though the job of a software tester is to catch errors committed by developers, software testers themselves are not immune to errors. As a beginner in software testing, you would make your own mistakes and learn from them to shape your career path.

In the test automation tool market, Selenium is most likely to be the first tool of choice for testers. Selenium is useful for writing test scripts for web applications. It is capable of simple tasks—like checking how the page loads, to a more complex process—like imitating the entire user experience on a website. Over the years, Selenium has evolved to more than just an automation tool to a much-needed testing skill for QA professionals.

Development can successfully remove the bottlenecks created by waterfall methodology by improving development productivity through encouraging collaboration,continuous feedback loops, and automating processes. Collaboration. Feedback. Automation. These are the main building blocks of Development operations. However, not all Development implementations are successful. Why? Building blocks are not enough. You need to take these building blocks and design a Development pipeline that suits your needs.

There are no silver bullets to solve your data issues in this Big Data world. This truism became repeatedly apparent in Searcher Seismic’s journey towards better data management. We realized that every choice has compromises associated with it, and a robust solution will necessarily integrate many individual pieces of technology and business processes. Having said that, there are some solutions that are undeniably better than others.