- December 21, 2015
In a Q&A, big data and data science expert Kirk Borne discusses new data processing and analytics technologies and the growing importance of data literacy in organizations.
- December 09, 2015
If Hadoop and Spark are to sneak into the enterprise, they will need to be manageable. With Driven, Concurrent Inc. takes a stab at the problem.
- December 02, 2015
Business analysts and data scientists no longer restrict themselves to internally produced data that comes from IT-managed production systems. For their analysis they use all the data they can lay ...
- November 16, 2015
IBM's planned purchase of The Weather Co.'s data operations may be a bellwether event from which data professionals can learn.
- October 30, 2015
At its Insight 2015 conference, IBM featured Apache Spark, releasing a cloud-based Spark service to support analytics applications and detailing Spark use in some of its own tools.
Sponsored by CloudHealth - As enterprises continue to add new use cases and workloads to their cloud portfolio, the stakes keep rising for potential governance speed bumps. Business users and IT professionals alike are now using the cloud for everything from compliance and security to cloud-native application development and infrastructure optimization. But this makes policy management more difficult, time consuming and costly, especially with so many cloud services being purchased and deployed outside the scope, visibility and control of a centralized IT operations group. See More
Sponsored by CloudHealth - In the era of Cloud 1.0, early adopters were often drawn to the cloud because it allowed them to reduce Capex and move to a more predictable subscription pricing model. In recent years, cloud adoption has surged because organizations have recognized that it not only reduces their hardware purchases and per-seat software licenses but provides many operational benefits as well. See More
Sponsored by CloudHealth - For more than a decade, the biggest gating factor in cloud computing adoption was perceived security risks. IT professionals and business leaders alike were often extremely concerned about a perceived loss of control of mission-critical data and essential applications when moved to the cloud. See More
- October 27, 2015
Dell and others have a new ETL reference architecture. Its purpose is to ease migrations to Cloudera Hadoop. Also: Dell buys EMC; Syncsort is acquired.
- October 19, 2015
We may have outlived the era of killer apps in some part defined by Walmart, but Hadoop big data applications may help the giant's quest for more growth.
- October 13, 2015
MapR takes JSON format data into Hadoop, while Teradata places its flagship database on AWS.
- October 12, 2015
Not so long ago I attended a session in which the speaker was very clear on what big data is and what it is not. In his opinion, big data is unstructured data and unstructured data is big data. ...
- October 07, 2015
Tracking 'What is Hadoop?' is getting more complex as the potential components of Hadoop systems increase -- and core elements such as HDFS are augmented by possible alternatives.
- October 05, 2015
The third big data myth in this series deals with how big data is defined by some. Some state that big data is data that is too big for a relational database, and with that, they undoubtedly mean a ...
- September 30, 2015
The latest version of MongoDB finds the NoSQL database running on a new WiredTiger storage engine. Better performance and data compression are among MongoDB 3.0's touted benefits.
- September 30, 2015
The DataStax Cassandra engine, officially called DataStax Enterprise, is now Spark-certified. The move is one of several for the NoSQL database on a possible upswing, further evidenced by a new deal with Microsoft.
- September 28, 2015
Self-service analytics allows users to design and develop their own reports and do their own data analysis with minimal support by IT. Most recently, due to the availability of tools, such as those ...
- September 22, 2015
At a TDWI Boston Chapter meeting, Mark Madsen says some notions of information become outdated in the face of big data analytics. This is part one of two.