No, you shouldn’t keep all that data forever Modern ethos is that all data is valuable, should be stored forever, and that machine learning will one day magically find the value of it. You’ve probably seen that EMC picture about how there will be 44 zettabytes of data by 2020? Remember how everyone had Fitbits […]
IDG Contributor Network: How in-memory computing drives digital transformation with HTAP In-memory computing (IMC) is becoming a fixture in the data center, and Gartner predicts that by 2020, IMC will be incorporated into most mainstream products. One of the benefits of IMC is that it will enable enterprises to start implementing hybrid transactional/analytical processing (HTAP) […]
IDG Contributor Network: Are you treating your data as an asset? It’s a phrase we constantly hear, isn’t it? Data is a crucial business asset from which we can extract value and gain competitive advantage. Those who use data well will be the success stories of the future. This got me thinking: If data is […]
Spark tutorial: Get started with Apache Spark Apache Spark has become the de facto standard for processing data at scale, whether for querying large datasets, training machine learning models to predict future trends, or processing streaming data. In this article, we’ll show you how to use Apache Spark to analyze data in both Python and […]
IDG Contributor Network: A speedy recovery: the key to good outcomes as health care’s dependence on data deepens It may have been slow to catch on compared to other industries, but the health care sector has developed a voracious appetite for data. Digital transformation topped the agenda at this year’s Healthcare Information and Management Systems […]
What is Apache Spark? The big data analytics platform explained From its humble beginnings in the AMPLab at U.C. Berkeley in 2009, Apache Spark has become one of the key big data distributed processing frameworks in the world. Spark can be deployed in a variety of ways, provides native bindings for the Java, Scala, Python, […]
Review: H2O.ai automates machine learning InfoWorld Machine learning, and especially deep learning, have turned out to be incredibly useful in the right hands, as well as incredibly demanding of computer hardware. The boom in availability of high-end GPGPUs (general purpose graphics processing units), FPGAs (field-programmable gate arrays), and custom chips such as Google’s Tensor Processing […]
Dremio: Simpler and faster data analytics Now is a great time to be a developer. Over the past decade, decisions about technology have moved from the boardroom to innovative developers, who are building with open source and making decisions based on the merits of the underlying project rather than the commercial relationships provided by a […]
Apache PredictionIO: Easier machine learning with Spark The Apache Foundation has added a new machine learning project to its roster, Apache PredictionIO, an open-sourced version of a project originally devised by a subsidiary of Salesforce. What PredictionIO does for machine learning and Spark Apache PredictionIO is built atop Spark and Hadoop, and serves Spark-powered predictions […]
R tutorial: Learn to crunch big data with R A few years ago, I was the CTO and cofounder of a startup in the medical practice management software space. One of the problems we were trying to solve was how medical office visit schedules can optimize everyone’s time. Too often, office visits are scheduled to […]
IDG Contributor Network: Your analytics strategy is obsolete In the information age, it’s the data-driven bird that gets the worm. Giant companies like Google, Facebook, and Apple hoard data, because it’s the information equivalent of gold. But merely hoarding data isn’t enough. You need to be adept at sifting through, tying together, and making sense […]
IDG Contributor Network: ETL is dead Extract, transform, and load. It doesn’t sound too complicated. But, as anyone who’s managed a data pipeline will tell you, the simple name hides a ton of complexity. And while none of the steps are easy, the part that gives data engineers nightmares is the transform. Taking raw data, […]
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