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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 2008 Archives

In the last quarter of 2007, I had listed Operational reporting as a leading BI project for 2008 across the industry. Though I have no official surveys to check against, the feeling from the industry is that more companies are seeing the need for operational reporting and there is one project somewhere in the organization which is an operational reporting project.

As companies start doing more operational reporting, there are a few issues that come to mind

1. Data quality
2. Data consistency
3. Data completeness
4. Metadata
5. Master Data (of any kind)

All of the above play a role in the operational reporting process. Data quality covers bullets 2 and 3 in its own space. But if you have metadata and master data related needs, they are critical components to the success of your operational reporting.

Bottom line, we need to draw attention to the fact that you need organizational data alignment and a data governance committee that can really drive the process. As we move forward in the BI space, please bear in mind that your data drives your business. Having a good data strategy is critical to all the BI projects in your organization.

There are a number of books, whitepapers, articles on this subject and I encourage your to read up on this subject, no matter what level of maturity you are at in your BI projects.

Posted March 31, 2008 6:28 PM
Permalink | 1 Comment |

An spurt of activity is seen in the analytic appliances area. There are a number of companies working on this technology space in stealth mode. Why is all of this attention in this subject, is a matter worth discussing.

There are several key factors here, notable among them are

1. BI Acquisitions - With SAP and IBM acquiring players like BO and COGNOS, there is more room for new companies to compete with offerings.

2. Predictive Analytics - This area is going through a second coming. With the ability to process large volume of data, analytic appliances may provide a robust platform for predictive analytics.

There are more thoughts here to discuss. Let us see how this market shapes this year with the current established players and the yet to enter competition. Till then, your perspectives are welcome comments in this discussion.

Posted March 17, 2008 8:41 PM
Permalink | No Comments |

Data management and architecture is becoming a nightmare for corporations. While the demand for more volumes of data at a greater detail keeps driving the IT resources, there are several issues that often get put on the shelf since the price point to manage the data and get it through the data warehouse becomes the focus of the implementation.

What can we do about the data management conundrum. Setting up a Data Steward office brings a point owner and a governance body brings the quality, teamwork and the ability to prioritize the data demands. What can you do when you drink from a garden hose which switches to a fire hose?

This is both a business and technology problem. While the business problem needs to be addressed, this blog will overflow if we discuss that aspect alone. A technology solution to the problem is available in the data warehouse appliance platform. User education needs to be a prime goal to help the blackbox become transparent, but once the understanding is there, the solution architecture becomes self evident.

How we can accomplish this and more will be discussed another day.

Posted March 12, 2008 7:45 AM
Permalink | 1 Comment |