Data Quality in the Data Lake
It’s been a few months since data migration and integration vendor Syncsort completed its acquisition of Data Quality solutions vendor Trillium Software. The combination of the two vendors is already proving a good fit, mirroring where the industry is going, according to Harald Smith, Director of Product Management at Trillium. As he explains it, Syncsort […]
Read More →Syncsort’s New Change Data Capture Capabilities Extend Leadership in Mainframe Access
by Angela Guess According to a recent press release, “Syncsort, a global leader in data liberation, integrity and integration solutions for next-generation analytics, today announced new capabilities in its unrivaled mainframe data access and integration solution that continuously, quickly and efficiently populates Hadoop data lakes with changes in mainframe data. The new DMX Change Data […]
Read More →Hadoop and Enterprise Information Management: Leveraging Big Data Solutions
The past few years have firmly established the importance of Big Data in the global business environment. 2017 looks to be the the year of greater Apache™ Hadoop implementation (both in terms of its open source development and more available commercial options) at the enterprise level, as Enterprise Information Management (EIM) continues to need more […]
Read More →Syncsort Delivers Solutions Supporting Data Governance and Customer 360 Initiatives
by Angela Guess According to a recent press release, “Syncsort, a global leader in data liberation, integrity and integration solutions for next-generation analytics, today announced new solutions that bring together its industry-leading Big Data Integration and Trillium data quality software to address enterprise requirements to support data governance and Customer 360 initiatives in the data […]
Read More →PSSC Labs Announces Enterprise Server Designed Specifically for Hadoop with 240TB of Storage
by Angela Guess According to a new press release, “PSSC Labs, a developer of custom HPC and Big Data computing solutions, today announced the next generation of its CloudOOP Big Data Server Line – the CloudOOP 24000. The next iteration of the company’s industry leading CloudOOP 12000, the only Enterprise server platform engineered specifically for […]
Read More →Data Warehouse vs. Data Lake Technology: Different Approaches to Managing Data
Solving business problems using Big Data depends upon the approach taken. For example, if an organization only knows Data Warehouses, then challenges will be framed to fit using a Data Warehouse. As Abraham Maslow, a prominent psychologist eloquently said “I suppose it is tempting, if the only tool you have is a hammer, to treat […]
Read More →Who Won the Debate Between Apache Spark and Hadoop?
Click to learn more about video blogger Andrew Brust. The Big Data & Brews video blog series continues with host Andrew Brust, Senior Director of Market Strategy and Intelligence. The series touches on hot topics within the business of Big Data, Analytics, Internet of Things, Machine Learning, Cloud Computing, Modern BI, NoSQL and Next Generation Technologies. In […]
Read More →The Role of Big Data Performance in DevOps Production
Ash Munshi, CEO, and Chad Carson, co-founder of Pepperdata, recently spoke with DATAVERSITY® about the state of Big Data performance and DevOps, what’s on the horizon, and Pepperdata’s role in that future. Big Data Expansion Munshi and Carson see lots of companies experimenting with getting into the Big Data space, mostly with consumer-facing data first […]
Read More →Case Study: Implementing Data Governance for Data Lakes and Big Data
Shannon Fuller says that knowing what your priorities are is the key piece to efficient development of a governance structure for the Data Lake. Fuller is the Director of Data Governance at Carolinas Healthcare System, where he piloted an HDInsight Hadoop implementation on Microsoft Azure. Speaking at the DATAVERSITY® Enterprise Data Governance Online 2017 Conference, […]
Read More →Weaving Your Own Big Data Fabric
Click to learn more about author Ravi Shankar. With Big Data, anyone with a modest budget can store, manage, and process vast amounts of data. The problem is, many companies are storing data from different systems in different formats, creating Big Data silos that results in large datasets that need to be integrated manually. Aside from […]
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