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.

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.

An exciting day today as Qlik launches the first-ever “History of the Fortune 500” as the official analytics partner of the Fortune 500. This unique data analytics site offers a window into the companies that have shaped America and the history that shaped them.

With COVID-19 now part of our daily lives, normal business operations and practices have been abandoned or curtailed and reinvented to sustain our businesses. Indeed, each department, division and team has had its own dynamics changed in this time of lockdown, and coping with process and workplace setting changes can present unique challenges.

The importance of digital banking and electronic commerce has proven all the more important during the pandemic. Online shopping is the only choice in many cases for conducting commerce. A recent McKinsey report, pre-COVID 19 outbreak, revealed that retail digital banking acceptance was already high. It has increased to the point where 60% of customers under the age of 70 use digital channels. That number increases to 75% for those under the age of 50.

With the Oil and Gas Industry facing some unprecedented times and challenges with the price of crude oil, a slowing economy, and a forecasted decrease in the global market demand, there is a greater focus on a margin-based than production-based business. To address these constant challenges, new ways of thinking must be adopted to improve operational efficiency.

Apache HBase became a top-level project with Apache 10 years ago and Cloudera began contributing to it at the same time (2010). Over this time, it has become one of the largest and most popular open-source tools in big data and one of the most popular NoSQL databases.

People intuitively know that self-driving or autonomous cars present complex engineering challenges. Vehicle assembly is the easy part – we’ve been doing that for 100 years. The real challenge is a data challenge, acquiring and managing the data needed to run the vehicles’ brain, eyes, and ears. Autonomous driving technology complexity lies in the ability to ingest, store, analyze, and deploy large volumes of data & the high bandwidth needs of data-in-motion.

Today’s globalized organizations demand a new standard for communicating and sharing information. That includes data-rich content that moves through environments, networks, and locales. From being stored, analyzed, and shared, to quickly and effectively moving between environments, to spinning up in clusters and informing endless applications—data is more critical than ever.

This blog post is part of a series on Cloudera’s Operational Database (OpDB) in CDP. Each post goes into more details about new features and capabilities. Start from the beginning of the series with, Operational Database in CDP. This blog post gives you an overview of the languages, frameworks, and applications supported by Cloudera’s OpDB.