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Oracle Goes All In On Cloud

October 18, 2016 by Dave Menninger

I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18...[read more]


The Benefits of Semantic-Based Data Modeling in the Smart Data Lake Era

October 18, 2016 by Sean Martin

The driving force behind enterprise data analytics today is obtaining valuable insights more quickly from large, diverse data sets. A key issue blocking easier access for data scientists, business analysts and IT has been finding an alternative to the current data modeling process.[read more]

The New Mainstream Appeal of Apache Spark

October 13, 2016 by Rick Delgado

It wasn’t too long ago that big data was thought of as a niche concept, something reserved for only those companies that were especially tech-savvy. Fast forward a few years and the popularity of big data has increased tremendously, with businesses of all shapes and sizes using it. Such is the way with most technologies, and Apache Spark...[read more]

Teradata Takes On Cloud and Developers with Big Data & Analytics

September 23, 2016 by Dave Menninger

Teradata recently held its annual Partners conference, at which gather several thousand customers and partners from around the world. This was the first Partners event since Vic Lund was appointed president and CEO in May. Year on year, Teradata’s revenues are down about 5 percent, which likely prompted some changes at the company....[read more]

A Recipe for Cooking with the Hadoop Ecosystem

August 26, 2016 by Dave Menninger

It’s part of my job to cover the ecosystem of Hadoop, the open source big data technology, but sometimes it makes my head spin. If this is not your primary job, how can you possibly keep up? I hope that a discussion of what I’ve found to be most important will help those who don’t have the time and energy to devote to this wide-ranging...[read more]

Big Data Projects – When You're Not Getting the ROI You Expect

August 8, 2016 by Paul Barsch

Some failing big data projects get millions more pumped into them with the hope that they’ll break even. At some point good money needs to stop chasing bad projects, but it takes leadership to make the right decision.[read more]

Retail Data Monetization: Are you sitting on top of a retail goldmine?

June 28, 2016 by Ajith Nayar

The majority of sales generated in the 4.5 trillion dollar US retail market is in-store and the volume of transaction data collected at various points in the trading process is immense. This data is a treasure trove of customer insight as well as product performance. While many retailers mine this data to gain specific insights into understanding their shoppers better, the possibilities that such data analysis opens up is largely untapped.[read more]

Apache Spark and Hadoop: The best big data solution for enterprises

June 1, 2016 by Jagadish Thaker

The term big data has become the center of attention for enterprises. In the past, business decisions have been made on the basis of transactional data stored in relational databases. This is known as traditional data, which is in structured form and easy to analyze for getting business insights.Apart from this critical business data,...[read more]


Five Steps to Successfully Manage Multiple Data Platforms

April 13, 2016 by Kevin Petrie

We data folks live in exciting times.As we saw at the Strata + Hadoop show in San Jose, open source developers continue to deliver new ways to analyze high volumes of fast-moving data.One of the hottest, Apache Kafka, can feed data from thousands of applications to emerging platforms like HBase and Cassandra. Enterprises can use Kafka...[read more]

Apache Drill vs. Apache Spark: What’s The Right Tool for the Job?

March 1, 2016 by Jim Scott

If you’re looking to implement a big data project, you’re probably deciding whether to go with Apache Spark SQL or Apache Drill. This article can help you decide which query tool you should use for the kinds of projects you’re working on.[read more]

Preparing Yourself to Move to Apache Spark

February 29, 2016 by Jim Scott

While MapReduce has been the mainstay of Hadoop processing, Apache Spark is now taking the throne as the way to handle distributed computation. The reasons are obvious: Spark is very fast due to its use of Resilient Distributed Datasets, or RDDs, and it has a clean programming model.[read more]

A Guide to Spark Streaming - Code Examples Included

February 25, 2016 by Jim Scott

Apache Spark is great for processing large amounts of data over large clusters, but wouldn’t it be great if you could process data in near real time? You can with Spark Streaming.[read more]


Big Data and Hadoop Development 2016

December 16, 2015 by Jenny Brown

Solving the Hadoop challenges and shortcomings with SAS will allow you to make the most of Big Data and use it as a catalyst to bring about positive outcomes of organizational growth, profit and development.[read more]


Hadoop and Spark: Better Together

October 1, 2015 by Jim Scott

The various online reports about the end of Hadoop as a big data framework bring to mind Mark Twain’s notable quote about the reports of his demise being an exaggeration. Hadoop is very much alive, and numerous organizations continue to make it a key component of their big data and analytics initiatives.[read more]

Managing Big Data Integration and Security with Hadoop

September 2, 2015 by Jason Parms

An open-source framework like Hadoop offers endless possibilities for development, and with a strong management group like Apache Systems behind it, one can expect increasing numbers of modules and technologies to integrate with Hadoop to enable your business to achieve its Big Data goals – and maybe even go significantly beyond what you can envision today.[read more]