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Data Warehousing

The USA Is Building the World's Fastest Supercomputer

September 30, 2015 by Xander Schofield

The United States president, Barack Obama, wants a new supercomputer for the United States and signed an executive order for that purpose. The initiative is known as the NSCI (National Strategic Computing Initiative) with the goal of ending up with an exaflop supercomputer, which means a machine that is around thirty times faster than the current one.[read more]


Big Intelligence: BI Meets Big Data, with Apache Drill

September 18, 2015 by Jim Scott

A new world of data exploration and insights is here. Out with the old and small data, in with the new, Big Data. Data analysts have become one of the greatly demanded occupations of our new digital age. Come learn about a few of their tools of the trade.[read more]

Forecast Product Demand with Confidence

September 9, 2015 by Keith Peterson

Is your company using demand forecasting in your planning process? And are you happy with those results? Based on our interviews with hundreds of companies worldwide, we have found that among midsize manufacturers and distributors, many still use error prone spreadsheets or forecast based on historical sales data.[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]


Less Dogma Equals Better Decision Making

August 17, 2015 by Paul Barsch

Some of the biggest breakthroughs come as a result of challenging assumptions; especially those that are commonly accepted. But first you'll need to put processes, systems and people in place to continually overcome preconceived notions.[read more]

Automate the Boring But Essential Parts of Your Data Warehouse

August 12, 2015 by Keith Peterson

To deliver on your company’s future demands for data and insights, you will need to maintain your existing data warehouse – and add the great new capabilities available with big data management and in-memory analytics. The real opportunity is in making those technologies work together smoothly with minimum effort and risk.[read more]

Amazon's Cloud Computing Giant is Getting Closer to Full Takeover

August 7, 2015 by Xander Schofield

Not many know that Amazon Web Services, Amazon’s cloud computing franchise, is just less than a decade in age and already taking a commanding lead among its peers. Amazon has indicated that in the first quarter of 2015, it made $1.57 billion with a profit of $265 million from 2014’s $1.05 billion sales within the first quarter and a profit of $245 million. Nonetheless, Amazon Web Services’ margins had dipped to 16.9 percent from those reported in 2014’s first quarter that stood at 23.3 percent.[read more]

Want More Actionable Information from Your BI? Support Your IT Team’s Need for Data Warehouse Automation

August 6, 2015 by Keith Peterson

If your organization is relatively new to BI but has successfully built some new reports with one of the great visualization tools on the market, you will soon find yourselves in need of a better data organization environment.[read more]

Using Procurement Analytics to Simplify Your Supplier Reconciliation

July 20, 2015 by Keith Peterson

Ask finance managers to name a necessary evil of their responsibilities and many will cite reconciling goods received against invoices not received (“GR-NI”). The GR-NI issue is time-consuming to manage but not exactly mission critical to finding new business.[read more]

Challenges of Working with Big Data: Beyond the 3Vs

July 16, 2015 by Venky Ganti

Among many challenges in working with big data, the 3V’s (Volume, Velocity, and Variety) have gotten a lot of attention. Googling yields many results worth reading. Almost all of these focus on technological challenges in managing and processing big data. In this post, I would like to highlight a different set issues that make working with big data challenging, even if the underlying infrastructure is admirably able to handle all three V’s.[read more]


What’s an IT Data Warehouse? And Why Do You Need One?

June 19, 2015 by Sadanand Sahasrabudhe

Data warehouse.

In the course of running IT operations for your business, systems collect a wealth of data – data that can yield useful insights to help understand how you deliver services, lower costs and drive more innovation. By analyzing this data effectively, you can get a 360-degree view of the IT business.[read more]

10 Reasons Why Now Is the Time to Get into Big Data

June 12, 2015 by Rick Delgado

Big data is a key that'll explain specifically what your consumers really think about your product. Big data is even being used in medical research for companies that do personalized medicine or companion diagnostics, and need to analyze large amounts of biological data. You'll be able to use your insight to easily get a better picture of your customers based out of different geographic areas and belonging to different demographic groups.[read more]

Solving Supply Chain Risks [INFOGRAPHIC]

June 4, 2015 by Keith Peterson

This infographic provides an overview of the most prevalent supply chain risks, the departments they affect, their financial impact on your business, and how they can be resolved.[read more]


Will You Always Save Money with Hadoop?

May 27, 2015 by Tamara Dull

The Big Data MOPS Series.

If you answered “yes” to the question posed in the title, you’re right. Because if you’re talking about the open source Apache Hadoop project (and any related open source project) , you can download the software for free, take advantage of the free licensing, and run it on low-cost commodity hardware.[read more]


A Big Data Cheat Sheet: What Executives Want to Know

May 21, 2015 by Tamara Dull

The Big Data MOPS Series. 

What can Hadoop do that my data warehouse can’t? The short answer is: (1) Store any and all kinds of data more cheaply and (2) process all this data more quickly (and cheaply). The longer answer is: They say that 20% of the data we deal with today is structured data. I also call this traditional, relational data. The other 80% is semi-structured or unstructured data, and this is what I call “big” data.[read more]