Learn how and when to apply transformations in your data strategy

The COVID-19 pandemic has forced government organizations to reassess their strategies, plans, and aspirations for digital transformation. Despite this uncertainty, IT leaders must quickly identify and act on strategies and plans that lead to positive outcomes. In many cases, governments will expand the role of digital technologies in service and program delivery.

Evaluating anomalies and unpredicted events like pandemics and ESG concerns In part II of the series, we sat down for an interview with Dr. Richard Harmon, Managing Director of Financial Services at Cloudera, to find out more about how the industry is adopting new technology. You can catch-up and read part 1 of the series, here. Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon.

With only about 35% of machine learning models making into production in the enterprise (IDC), it’s no wonder that production machine learning has become one of the most important focus areas for data scientists and ML engineers alike. As you may remember, we recently announced a full set of MLOps capabilities in Cloudera Machine Learning, our cloud native machine learning tool for the cloud.

Today, we announced the acquisition of the assets and IP of Knarr Analytics, an innovative start-up that provides real-time collaboration, sophisticated data exploration and insight capture capabilities, to complement Qlik’s cloud data and analytics platform.

Depending on your projects and your QA team’s nature, your choice of automation testing tool must be compatible with many different aspects, such as project scope and requirements, in addition to its reputation. The best tool available does not guarantee the best testing outcome. It must be the right one.

In the last blog with Deloitte’s Marc Beierschoder, we talked about what the hybrid cloud is, why it can benefit a business and what the key blockers often are in implementation. You can read it here.

Modern businesses face a continuously growing mountain of data, made up of many different operational processes and performance metrics, which your users need to decipher for insights and proactively monitor in order to ensure business goals are met. Embedded dashboards are one way for your users to keep track of key information while using your application.

If your company has already started getting into machine learning / deep learning, you will quickly relate to the following story. If your company is taking its first steps into data-science, here is what is about to be dropped on you. If none of the above strikes a chord, well it’s probably good to know what’s out there because data-science is all the rage now, and it won’t be long until it gets you too 🙂

Continuous Testing is the process of testing at all stages of software development – one after the another- without any human intervention. Continuous Testing is key to faster delivery of Agile products to the market. Continuous Testing makes it possible to eliminate testing as a bottleneck for faster software development and delivery. But the path to achieving Continuous Testing has its own challenges, most common of which are mentioned below.