Blogs

Top 5 trends that are making life easier for data professionals

Top 5 trends that are making life easier for data professionals

August 7, 2015 | by Kimberly Madia, Worldwide Product Marketing Manager, InfoSphere Streams, IBM
An ever-changing business environment is forcing data professionals to rethink their work methods—but fortunately, help is available. Here are five trends that are making life easier for data professionals: the emergence of Apache Spark, opportunities for greater skill reuse, growth in online and...
Merging datasets using graph analytics

Merging datasets using graph analytics

July 27, 2015 | by Daniel Darabos, Software Engineer, Lynx Analytics
Using Apache Spark, we built an end-to-end fingerprinting tool to identify matching candidates among two independent data sets, calculating a similarity score and solving the stable marriage problem. Integration with a graphical environment not only saved us time, but also allowed us to easily...

How Spark is tuning up the logical data warehouse

July 21, 2015 | by James Kobielus, Big Data Evangelist, IBM
Apache Spark will become a core technology in the logical data warehouse (LDW), and its sweet spot is as the workbench of choice for data scientists who interactively and iteratively explore, build and tune statistical models for machine learning, graph and streaming analytics.
Analyzing time series data with stream processing and machine learning

Analyzing time series data with stream processing and machine learning

July 21, 2015 | by Jim Sharpe, President., Sharpe Engineering Inc.
Time series data can contain highly valuable insights—if organizations can detect and classify the events within it. An approach that combines stream processing and machine learning holds the key to analyzing large, fast data streams.
Context is key to deriving analytic value with Hadoop

Context is key to deriving analytic value with Hadoop

July 15, 2015 | by David Birmingham, Senior Principal Consultant, Brightlight Business Analytics, a division of Sirius Computer Solutions
Big data without context is pretty much useless, especially when that context can fluctuate so widely—which is why the role of Hadoop in creating accurate analytics is crucial for deriving value from big data.
Spark and Hadoop: Taking big data to the next level

Spark and Hadoop: Taking big data to the next level

June 30, 2015 | by Peter Schlampp, Vice President of Product, Platfora
Spark is one of the key enablers of Hadoop’s journey from the Trough of Disillusionment to the Plateau of Productivity. Together, Spark and Hadoop are taking big data to the next level.
Spark and the crux of differentiation

Spark and the crux of differentiation

June 23, 2015 | by James Kobielus, Big Data Evangelist, IBM
IBM is investing deeply in Spark in a wide range of long-term initiatives. Discover how IBM’s long history of joining powerful, innovative open-source projects allows it to create markets by contributing significant technological improvements and supporting business solutions.
9 reasons why developers and data scientists are primed to spark insight with Spark

9 reasons why developers and data scientists are primed to spark insight with Spark

June 19, 2015 | by James Kobielus, Big Data Evangelist, IBM
An open-source software platform called Apache Spark is growing rapidly in popularity as an essential platform for rapidly modeling, exploring and analyzing data. Here are nine reasons why developers and data scientists are primed to #SparkInsight with Spark.
Spark Summit 2015, Day 2: A gathering of today’s most dynamic data scientists

Spark Summit 2015, Day 2: A gathering of today’s most dynamic data scientists

June 18, 2015 | by James Kobielus, Big Data Evangelist, IBM
On Tuesday, I plunged right back into Spark Summit—which, if anything, was buzzing more vigorously with interesting content than it had been the day before. Not surprisingly, IBM’s Spark announcements were the talk of the show.
Spark Summit 2015, Day 1: Energizing a new wave of data scientists

Spark Summit 2015, Day 1: Energizing a new wave of data scientists

June 17, 2015 | by James Kobielus, Big Data Evangelist, IBM
A growing body of fresh thinking is coming down the pike. Much of it will come from the droves of IBMer data scientists who participated in the recent and wildly successful internal Hack Spark Challenge, as well as ongoing IBM-sponsored hackathons, meetups and developer days focusing on Spark.

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