I just finished presenting at the TDWI “Cool BI” Forum in Chicago this week.  I had an interesting conversation after my presentation about identifying where to look for big data opportunities within one’s organization.  I’m a big advocate of starting with the annual report, and I’ll use this blog to discuss 1) where to look in the

In my discussions about the assault of big data technologies on the traditional Business Intelligence (BI) and data warehouse (DW) markets, sometimes it is hard to identify specific use cases where a big data technology – like Hadoop – can help your BI environment.  Many of these big data use cases are really still being

A recent blog that I wrote, titled “The Coming BI Tsunami,” drew a quick response from my old friend Warren Thornthwaite.  Warren and I worked together back in the 1980’s at Metaphor Computer Systems, one of the first (if not the first) Data Warehouse (DW) and Business Intelligence (BI) company.  Warren has spent much of

In this the final series on the Big Data MBA, let’s use a case study to understand the power of combining Porter’s Value Chain Analysis with his Five Forces Analysis.  One of the noted deficiencies of Porter’s Value Chain Analysis (see Greg Satell’s article titled “The Semantic Economy”) is that it doesn’t give serious enough

This is the third in the series of four blogs that I’m writing on the “Big Data MBA.”  My first blog, “Big Data MBA: Course 101A,” covered the use of the “Big Data Worksheet” as a business valuation technique to help your line of business (LOB) users envision where and how big data analytics can

Big Data Turns Conventional BI Thinking On Its Head I’m taking a short break from my “Big Data MBA” series to provide some thoughts from the recent Gartner BI Summit.  Maybe it was because I just came from the Strata conference, or maybe it’s because I spend most of my waking hours (and even some

As part of my continuing series on the “Big Data MBA”, I’d like to introduce a second business valuation technique.  My last blog, “Big Data MBA: Course 101A,” covered the use of the “Big Data Worksheet” as a business valuation technique to help your line of business (LOB) users envision where and how big data

I recently had the opportunity to present at the Strata conference in Santa Clara.  I was part of the JumpStart program, which was positioned as an MBA track for Big Data Scientists.  The title of my session was “Do it Right – Proven Techniques for Exploiting Big Data Analytics” (a link to a pdf of

In my previous InFocus blog, I talked about attending the EMC Education Services Data Scientist class titled  “Data Science and Big Data Analytics.”  The course provided a hands-on practitioner’s approach to the techniques and tools required for big data analytics.  My primary interest in the course was to see if it was really possible for

This past week I’ve had a chance to attend EMC Education Services new class titled  “Data Science and Big Data Analytics.”  The course provides a hands-on practitioner’s approach to the techniques and tools required for Big Data Analytics.  My primary interest in the course was to see if it was really possible to transition an

Given my Business Intelligence (BI) background (3 years at Business Objects as the head of their Analytic Applications business unit), I’m naturally drawn to conversations about how the world of big data is going to impact the BI world.  Now, the BI world has been taking quite a beating lately as the excitement surrounding the

Data quality and data governance just don’t get any love in the big data world. Compared with all of the technology innovations in Business Intelligence (real-time dashboards, mobile BI, advanced visualization), data warehousing (MPP architectures, in-memory computing, data virtualization), and advanced analytics (in-database analytics, Hadoop, NoSQL), poor old data quality just doesn’t seem exciting.  But

This is the time of year when many folks take a moment to be thankful for everything that we have, and to make plans for the year ahead.  On my jog this morning (a jog in only the technical sense as I was moving only slightly faster than the ladies walking next to me), I

My previous blog, “The Death of Why – Part I,” discussed how big data analytics is negating the need to understand “why” things happen.  With the vast amounts of detailed data available and high-powered analytic tools, it is possible to identify what works without having to worry about why it worked.  This can enable us

One interesting aspect of big data is how it is challenging the conventional thinking regarding how the non-analytical business user should be using analytics.  An article that I read in 2006 by Chris Anderson titled “The End of Theory: The Data Deluge Makes the Scientific Method Obsolete” really got me thinking about not only the

On November 9 I facilitated a Big Data Analytics Roundtable as part of a series that EMC Consulting is holding over the next few months. The goal is to help our clients better understand both the opportunities and challenges with respect to big data and advanced analytics. We had about 20 EMC customers participate in

One of my previous blogs, “Finding the Right Metrics”, talked about using analytics in the world of baseball to identify the metrics that are the best predictors of player performance, and how the field of sabermetrics has changed how the game of baseball is managed.  The result is that teams that deployed an analytics-led management

Before I continue my “Big Data Ramifications for Baseball” subject, there is a topic that I feel even more compelled to address.  I recently facilitated at EMC’s IT Leadership Council where I had the chance to mingle with a hundred-plus EMC customers. This allowed me the opportunity to poll a wide variety of industry leaders

Since we are in the middle of the major league baseball playoffs, and in honor of the recently released movie “Moneyball,” I thought it was only appropriate to discuss how the pursuit and identification of the “right” metrics has not only changed how the game of baseball is managed, but has the same potential impact

There seems to be this belief that big data and advanced analytics mean the end of the “Single Version of the Truth.”  I’ve heard several folks claim that the need to ingest massive volumes and variety of data in near real-time – necessitating more of an ELT approach versus the tradition ETL approach – obfuscates