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Krish Krishnan

"If we knew what it was we were doing, it would not be called research, would it?" - Albert Einstein.

Hello, and welcome to my blog.

I would like to use this blog to have constructive communication and exchanges of ideas in the business intelligence community on topics from data warehousing to SOA to governance, and all the topics in the umbrella of these subjects.

To maximize this blog's value, it must be an interactive venue. This means your input is vital to the blog's success. All that I ask from this audience is to treat everybody in this blog community and the blog itself with respect.

So let's start blogging and share our ideas, opinions, perspectives and keep the creative juices flowing!

About the author >

Krish Krishnan is a worldwide-recognized expert in the strategy, architecture, and implementation of high-performance data warehousing solutions and big data. He is a visionary data warehouse thought leader and is ranked as one of the top data warehouse consultants in the world. As an independent analyst, Krish regularly speaks at leading industry conferences and user groups. He has written prolifically in trade publications and eBooks, contributing over 150 articles, viewpoints, and case studies on big data, business intelligence, data warehousing, data warehouse appliances, and high-performance architectures. He co-authored Building the Unstructured Data Warehouse with Bill Inmon in 2011, and Morgan Kaufmann will publish his first independent writing project, Data Warehousing in the Age of Big Data, in August 2013.

With over 21 years of professional experience, Krish has solved complex solution architecture problems for global Fortune 1000 clients, and has designed and tuned some of the world’s largest data warehouses and business intelligence platforms. He is currently promoting the next generation of data warehousing, focusing on big data, semantic technologies, crowdsourcing, analytics, and platform engineering.

Krish is the president of Sixth Sense Advisors Inc., a Chicago-based company providing independent analyst, management consulting, strategy and innovation advisory and technology consulting services in big data, data warehousing, and business intelligence. He serves as a technology advisor to several companies, and is actively sought after by investors to assess startup companies in data management and associated emerging technology areas. He publishes with the BeyeNETWORK.com where he leads the Data Warehouse Appliances and Architecture Expert Channel.

Editor's Note: More articles and resources are available in Krish's BeyeNETWORK Expert Channel. Be sure to visit today!

March 2012 Archives

In the recent few months, there has been a lot of activity surrounding Big Data and the entire ecosystem. Several M&A's, new vendor announcements, capability enhancements and more. Along the way there has also been several announcements made by pure play Analytics community - including vendors, contributors and organizations, coming out in support of extending Analytical capabilities to the Big Data platform or including Big Data as part of Analytic source and data ecosystem. At a first pass, this seems to be a natural process, but do not wear your regular thinking cap and make these assumptions.

If you stand outside your normal periphery and look at Data, Big Data in particular, inspite of its sheer vastness in volume, velocity, variety, complexity and such, this data is very easily visualized and understood when seen through Analytics. Imagine for example, on Amazon.com your search has additional recommendations that are all textual in nature, you would be least interested in going back to Amazon.com, rather the data is presented as a statistic and has associated confidence factors, which makes it easy for you to shop there repeatedly. This is a simple example for this discussion on Why Analytics matters.

As you start looking for Big Data, remember to look for Analytics too, without the latter the former will never provide you useful insights.

Posted March 13, 2012 1:01 PM
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There has been all the buzz surrounding Big Data, and how it makes every organization look cool and competitive (that there are multiple layers of intricacies not withstanding). There are infrastructure providers,  community driven projects and associated support, research, venture capitalist backed vendors and much more happening.

While all this buzz is great and early adopters to this new and shiny object have made inroads, at a mass adoption level, Big Data has not been embraced yet by the business users. The reason for this being a key aspect of Visualization. One of the fundamental aspects that need to be understood here is the way we approach Big Data and its modeling and integration is very different from any other data integration exercise. Here is a simple way of looking at the difference

  •  Traditional Data Integration - Business Requirements & Analysis --> Model --> Organize--> Collect --> Integrate --> Store -->  Analyze --> Visualize
  •  Big Data - Collect --> Store --> Organize --> Visualize --> Analyze --> Business Requirements & Analysis --> Model --> Integrate --> Visualize
As you can see from the flow shown above, Big Data needs visualization before you can settle down for business requirements and post integration. You might wonder if this is really a huge problem or are we hyping this up, in reality this is a problem and there is very minimal options available at this point to provide as solutions. I do not want to classify any "App store" downloads as a robust solution, they are all driven towards a personal market for a consumer.

The reason for the current situation can be analyzed in two ways

  • Infrastructure Focus - Web 1.0 and 2.0 focused on infrastructure and the underpinnings, the OSI model and current solutions in the marketplace will definitely point that.
  • Data Ambiguity and Complexity - Big Data by nature is complex and ambigous, this requires additional efforts and deep SME's and sometimes Quants to think, integrate and solve. These folks need to able to visually analyze the data than reading machine data or long pages of text. The tools are not there yet for this purpose.
It is simply unfair to anyone to be looking at large sets of data to derive any value from the same. We need tools that can provide an interrogation platform for that data. The tools will and should be very ontology and semantic focused as we are not ready to model or integrate the data yet.

The journey ahead is greenfield still, there are a few vendors who are visionaries and among them there are a few who are considered leaders. In this year we will see a flurry of activity and investments in this side of the house. The frenzy of Big Data has not peaked yet but it is not too far in the future.

Posted March 3, 2012 6:37 AM
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