Tag: Hadoop

Google Cloud Leave a comment

HOW TWITTER DUMPED HADOOP TO ADOPT GOOGLE CLOUD

Source:-analyticsindiamag.com Back in May 2018, Twitter announced that they were collaborating with Google Cloud to migrate their services to the cloud. Today, after two years, they have successfully migrated and have also started reaping the benefits of this move. For the past 14 years, Twitter has been developing its data transformation pipelines to handle the load of its massive user base. The first deployments for those pipelines were initially running in Twitter’s data centers. For example, Twitter’s Hadoop file systems

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Kubernetes Leave a comment

Leveraging Kubernetes to Fuel Intelligence Everywhere

Source:-aithority.com Way back in 1992 when I was leading development for a shipping company, the Head of Sales forever changed the way I approached using data in our business environment. The request from Sales was simple enough. They needed to provide a breakdown of revenues, costs, largest customers, and some other attributes that could not be answered from any of our existing thousand plus reports. Worse, it would take 2-3 weeks to create a new report. The response from our

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Cloud Computing Leave a comment

The Power of Crunching Big Data Effectively

Source- insidebigdata.com According to an Accenture study, 79% of enterprise executives agree that companies not embracing big data will lose their competitive edge, with a further 83% affirming that they have pursued big data projects at some point to stay ahead of the curve. Considering that data creation is on track to grow 10-fold by 2025, it’s crucial for companies to be able to process it more quickly, and meaningfully. The expression “big data” is often bandied around in the business and tech

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Cloud Computing, DevOps, DevOps Tools Leave a comment

Containers help move Spark and Hadoop into analytics operations

Source:- techtarget.com Moving custom Spark and Hadoop pilot projects into production use has proved daunting. But container technology eased the transition at the Advisory Board analytics service. Spark and Hadoop analytics efforts often stumble when teams try to turn small pilot projects into larger operational apps meant for data science teams and business analysts. For many, it is an obstacle in their quest to work with big data. Configuration complexity has sometimes been the stumbling block. A custom-configured prototype built

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