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Data Warehousing

Why You Should Already Have a Data Governance Strategy

October 21, 2016 by Eran Levy

Garbage in, garbage out. This motto has been true ever since punched cards and teletype terminals. Today’s sophisticated IT systems depend just as much on good quality data to bring value to their users, whether in accounting, production, or business intelligence. However, data doesn’t automatically format itself properly, any more than...[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]

Demystifying Data Warehouses, Data Lakes and Data Marts

October 12, 2016 by Eran Levy

As data and analytics become a more integral part of business processes in an organization, so the non-DBAs among us might start to feel lost in a sea of technical terms which are frequently thrown around by technical teams.[read more]


Gaining the Millennial Digital Storage Market With Metadata and Tagging

October 3, 2016 by Jonathan Ring

It’s no longer enough to simply store data — you have to give people the ability to quickly and easily search through massive amounts of data and retrieve the information they need.[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]


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]


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]


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]


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]


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]


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]