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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!

February 2011 Archives

If you have noticed lately, there is a lot of buzz around "social media" data and large and small corporations have started lining up Twitter, Facebook and other social sites as a channel to connect to employees, customers and partners.

Put a pause to this hullabaloo. What is it that we are trying to convey through the social media channels? is there a context related to what we are sharing and does the context hold the appropriate relevance at the time ot writing and beyond? will all the trackback, commenst and wallposts bear any semblance to that context.

This is where the relevance of context to the content becomes a paramount piece of intelligence in the world of unstructured data. When you want to get intelligence out of the largesse, if you cannot establish context and relevance to the content, it is GIGO (garbage in and out). As you prepare to launch the social media exercise and establish more presence in the digital world, please ensure that content and context are always matched and available.

Posted February 28, 2011 4:28 PM
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It is alarming that electronic content is growing more by the second both inside and outside the enterprise. While 75% of this content may become "zero-value" over a period of time (depends on type of content - emails, documents, contracts, user guides), we need to understand which of these artifacts will make business sense and how to preserve the same. This is where tapping into the internal crowd becomes a necessity. Similar to how you have people providing ranking and scoring on the web about products, services and more, the internal crowd needs to rank and score content (internal and external) with the focus on its business relevance and value. Such and effort will lead to organizations gaining more efficiency in managing content and making such content more relevant.

There are a few "specific" applications that can do this, and they come with built in "content management" and "knowledge management" techniques and workflows. A whitepaper on one "up-start" will be available in about 2 weeks on my channel. If you are interested in specific details or more insights into this process, your comments and feedback are welcome.

Posted February 25, 2011 8:51 AM
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In the last few weeks, I have been asked this question by a number of people, "how do we justify the business case for Enterprise BI" or "how do we measure the value from Enterprise BI investments". The answer is quite simple to say - "BI brings insight into your business and enterprise performance". That answer is if we knew what we are doing and what to expect of outcomes from the exercise.

Sadly in many organizations, there is too much BI i.e too many silos doing the same effort. What this has led to is a state of chaos. Often when a new BI initiative is planned or suggested, the criticism is, "there have been multiple attempts and we failed, what makes you think this time we will be successful".

One of the first things to do is to get your house in an order. This is easier said than done, because each stakeholder wants to own or control their set of data and applications. Another level of complexity arises when each of these silos have their own metadata, taxonomy and business rules. The biggest hurdle often is to get a facilitated governance model to ensure that alignment occurs between the business stakeholders paving the way to a successful implementation of the BI program across the enterprise.

Large programs in organizations with global presence or even within regions of the world have been successful with a strong governance model for the program.

Once you have a governed initiative, measuring the value or ROI of such an investment is quantifiable across layers
  • Unified business metrics and measures
  • Unified business metadata
  • Reduced spend across the enterprise
  • Increased efficiency from data quality
  • Improved data processing cycles, resulting in predictable SLA's
  • Adoption of the BI platform, resulting in single version of truth
  •           Trust in data and associated business rules
  •           Business will own the data
Most organizations will quantify the ROI or value in terms of hard dollar returns in license cost savings or reduced hardware spend etc. My suggestion is to add the soft benefits to the justification factor for enterprise BI.

This is not a simple topic, this blog post is only a handful of suggestions. More comments or suggestions are welcome

Posted February 24, 2011 6:26 PM
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It is finally happening. The mainstream adoption of social analytics for business has started becoming a requirement in the world of business intelligence. There are major drivers for this adoption to happen at a quicker pace

  1. Mobile Devices - The emergence of mobile devices has led to a consumer revolution like never before. Consumers are now  able to express opinions on products, services and competition from wherever and whenever, and have become influencers in their communities of participation
  2. CRM for One Customer - Companies now want to go beyond sentiment analysis; in fact, the theme across CRM space is how to segment and market to one customer (i.e., personalized marketing and service offerings)
  3. Crowd Intelligence - Companies want to harvest the intelligence of the crowds. There are some stellar success stories - "IdeaStorm" and "InnoCentive"
  4. Software Emergence - TIBCO, Visible, Radian6, Nielsen, Webtrends, and much more. There are several software platforms that have emerged to provide the ability to link and gather data from social media
  5. Textual ETL and Processing - Inmon's textual ETL engine has provided a groundbreaking software to parse and process text and get the outputs to be stored into the DW platform. This provides a unique ability to integrate structured and unstructured data.
  6. Hadoop - A strong platform to store BIG data for processing. Provides a easy integration platform
  7. In-Memory Analytics - A new platform to support real time customer behavior and analysis
  8. Visualization - Spotfire, QlikView and Tableau have proven to be cool visualization tools for analyzing and reporting unstructured data
  9. Appliances Platform - DW appliances have found a purpose beyond just being a DW augmentation. The platform from any vendor is built to support BIG data, which is driving the user expectations to support social and unstructured data
In this year 2011, we are going to see and hear several success stories from organizations on social analytics.

Posted February 7, 2011 9:25 AM
Permalink | 1 Comment |