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Enterprise data architecture strategy and the big data lake

Today's enterprise data architecture strategy has to address how to align existing data systems with growing information needs, capabilities and data sources. Modern CIOs are faced with two challenges in unifying the increasingly disparate aspects of the enterprise data architecture. More>>

Syncsort open-sources Spark connector for mainframes

The clash between old and new gripping the analytics world moved up yet another notch this morning with the release of a connector from Syncsort Inc. that aims to make it easier for organizations to tap records in their mainframes using Apache Spark. It’s being made available under the same

Report: A data-driven culture is critical to Big Data success

Organizations have made big advances in Big Data analytics, but there’s still a long way to go even though many are already starting to see a significant impact on their bottom line. That’s the biggest takeaway from a new survey conducted by Forbes Insights, sponsored by Teradata Corp., in partnership

Data Cleansing vs Data Maintenance: Which One Is Most Important?

There are always two aspects to data quality improvement. Data cleansing is the one-off process of tackling the errors within the database, ensuring retrospective anomalies are automatically located and removed. Another term, data maintenance, describes ongoing correction and verification – the process of continual improvement and regular checks. Often, businesses

SAP embraces Hadoop with new in-memory analytics tool

A new tool from SAP will allow companies to analyze distributed Hadoop data alongside corporate data using the ERP giant's Hana in-memory computing platform. Announced on Tuesday, SAP Hana Vora is an in-memory query engine that taps the Apache Spark execution framework to deliver interactive analytics on Hadoop.More>>

Will the Rise of Spark Spell the End of Hadoop?

Spark has overtaken Hadoop as the most active open source Big Data project. While they are not directly comparable products, they both have many of the same uses. In order to shed some light onto the issue of “Spark versus Hadoop” I thought an article explaining the essential differences and

Why Do I Need A Data Lake?

The data lake is gaining lots of momentum across the different customers to whom I talk. Every, and I mean every organization wants to learn why and how to implement a data lake. But “because it is a cheaper way to store/manage data” is not a good reason

Don’t throw out design principles when jumping in Hadoop data lake

While there are often good reasons for technologies to change, useful skills are sometimes forgotten in the process. Today’s Hadoop data lakes may be a case in point, according to Joe Caserta, founder and president of New York-based consulting practice Caserta Concepts. He says advances in Hadoop-style data handling are

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