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Data Warehousing

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]

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Are Smart Data Lakes the Answer to Data Warehouses?

August 2, 2016 by Sean Martin

A phenomenal shift has occurred over the past few years in the enterprise data world. The ubiquitous data warehouses – the foundation for business intelligence and data discovery for several decades – are now becoming obsolete due to the emergence of data lakes. While both data warehouses and data lakes have their pros and cons, a new era of ‘smart’ data lakes based on semantic technology is emerging that can reduce the disadvantages of either, creating a clear path for the industry.[read more]

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Greening the Workplace 1.0: Going Paperless

July 11, 2016 by Chris Barry

Several new technologies allow you to transform your office into a less wasteful and more energy efficient space - and it starts with reducing paper usage.[read more]

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How Smart Data Lakes are Revolutionizing Enterprise Analytics

June 3, 2016 by Sean Martin

As the quantity and diversity of relevant data grows within and outside of the enterprise, business users and IT are struggling to extract maximum value from this data. Fortunately, recent developments in big data technologies have significantly impacted the proficiency of contemporary analytics – the most profound of these involving the deployment of semantically enhanced Smart Data Lakes.[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]

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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]

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Five Key Benefits of Retiring Legacy Applications to the Data Lake

April 6, 2016 by Sean Martin

With its promise to transform data management and analytics by providing access to all data across the enterprise, the data lake is quickly becoming more than just an industry buzzword.[read more]

How Hadoop Revolutionised IT

March 5, 2016 by Martyn Jones

This is the story of how the amazing Hadoop ecosphere revolutionised IT. If you enjoy it then consider joining The Big Data Contrarians.Before the advent of Hadoop and its ecosphere, the IT was a desperate wasteland of failed opportunities, archaic technology and broken promises.In the dark Cambrian days of bits, mercury delay lines and...[read more]

What Are Accumulators? A Must-Know for Apache Spark

February 27, 2016 by Jim Scott

If you’ve been using Apache Spark, then you know how awesome the Resilient Distributed Dataset (RDD) is. This data structure is essential to Spark for both its speed and its reliability. There are a couple of concepts that make Spark even faster and more reliable when run over large clusters: accumulators and broadcast variables.[read more]

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How to Stay Ahead of the Data Protection Curve in 2016

January 31, 2016 by Ryan Kh

2016 can be either your year for data security or for data theft. Some of that depends on luck. But much of your success or failure in this arena depends upon your preparedness and awareness of how data security is evolving. Security and theft are always stuck in a tug of war, an arms race which motivates both industries (and data theft most certainly is an industry) to alter and evolve their methods, to get a bigger piece of the pie than the other side has. In 2016, there are a lot of subjects which data security people are discussing, and you should be aware of some of them in order to keep you and your data safe.[read more]

In-House vs. Outsourced Call Centers: What to Choose

January 21, 2016 by Deepanshu Gahlaut

The Internet has also provided the option to outsource the call center services. This frees the company from managing an in-house call center staff and focus on other parts of the organization. Outsourced call center service providers are becoming really popular these days. Still it's not a decision that can be taken lightly. While these outsourced centers are more affordable, they often end up being negligent in quality control so many companies are staunch believers in having on-site call center staff even if it becomes cost ineffective, not willing to risk their brand’s reputation.[read more]

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72% of People Aren’t Familiar with Hosted VoIP

January 4, 2016 by Josh Rose

VoIP is the concept of using the internet and cloud based servers to place calls instead of using traditional pbx boxes and phone cables. A universally understood example being Skype which allows you to video or audio call anyone around the world over the internet for free.[read more]

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Is Big Data Winning or Losing?

December 9, 2015 by Josh Rose
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Big data is now used everywhere. AT&T has a database of 312 terabytes, the NSA use 30 million gigabytes a day and Facebook user share 30 billion pieces of content daily. There is big money and big opportunity in big data. Huge scale tools are being created all the time to benefit our existence and to make our lives easier. However these tools can sometimes be easier to cheat than other systems.[read more]

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A Closer Look at RDDs

November 20, 2015 by Jim Scott

Apache Spark has gotten a lot of attention for its fast processing of large amounts of data. But how does it get up to speed? The biggest reason that Spark is so fast is its use of the Resilient Distributed Dataset, or RDD.[read more]

Not Seeing the Results of Big Data? Maybe You Have a Lot of Data, Not Big Data

October 13, 2015 by Xander Schofield

Big data, everyone wants it, and most think they have it. But what you may have is simply a large quantity of data, not big data. Learn the difference and learn how to leverage both.[read more]