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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!

We are in the first week of the year 2014, wishing you all Happy New Year. The last year went by like a blaze and looking back there are several significant milestones that were created and exceeded in terms of technology and innovation. We now have Big Data integration, appliances and new techniques to analyze that data, creating business opportunities and leveraging new market. On the other hand while the data platform saw these changes, the infrastructure platform for Cloud computing grew in terms of features, a drive towards standards and gained more corporate nods for being an enterprise platform. The biggest equation that needs to be answered and is going to become the hottest topic is - Applications on Internet/Cloud or Data what drives us next? and where to?

In the next wave of innovations we will be seeing more from the Apps or Applications segment as opposed to the Data segment. The reason for this is the fact that you can deliver the value and insights to end users from all the data using analytics on dashboards and mashups as modern apps, and the result can be pushed to the recipient platform on demand or scheduled. Wait a minute, we can do most of this today and whats new? that's where I would like to draw your attention to focus on the analytics that can be delivered on cloud to mobile platforms. I'm talking about the dawn of next generation applications and the platform (atleast the first I played with and impressed is Enterpriseweb ) for creating a network application model that can be distributed and supported across the globe. This trend along with the devices that generate data from personal lifestyle to  BYOD at work will push the drive for Apps and Applications and the platform will be networked infrastructure and cloud based deployments. An interesting feature to think through here is the security features that need to be developed for this deployment and there are great opportunities here for new techniques and platforms to be designed for these requirements.

I will be visiting this topic periodically and invite your thoughts on the same.

Posted January 6, 2014 9:34 AM
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Last few months have been extremely busy on my calendar and one of the factors was the interview that I did with EnterpriseWeb and its cofounders Dave Duggal and Bill Maylk. This startup is having a vision of the next generation platform, where everything that happens in an organization is an event that can be indexed and searched by any business user at any point in time, and an adaptive platform is needed to provide the scalability and flexibility of this demand.

The platform that is built to handle the demands of a modern enterprise class workload, shows  the best in class architecture of combining the Zachman Architecture approach with web style REST API's and a semantic framework that can provide access to any data within the enterprise. This architecture also boasts of highly secure approach to protecting information that makes it a robust approach especially at the enterprise level.

The EnterpriseWeb platform has no compile time versus run time architecture, due to the fact that events occur in an enterprise in real-time. The underlying platform supports late binding features that make it simple to define and design dynamic applications that can provide value of high scale and magnitude to the end user.

Another feature of the architecture that is very impressive is the unified repository that surpassed expectations when it came to performance and scalability. The concept of one architecture for everybody simplifies the fact that many metadata management processes need to be implemented and followed in the enterprise. This approach in my opinion is the best way to manage semantic data in any size of organization.

Enterprise data today means data from within the enterprise and outside the enterprise including social media, web forums, 3rd party data, competitive intelligence data and more. In this model of data integration integrating data is relatively simple compared to traditional architecture approaches and one can build adapters for each type of data that needs to be integrated into the enterprise.

The overall goal of this company is to provide a new platform for the next generation architecture and after seeing the product demo and underlying architecture, it is definitely a robust and scalable architecture that can meet those goals. Feel free to visit the website and learn more. As I learn more about this architecture, I will post details in my blog or article.

Posted July 15, 2013 10:29 PM
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We are today standing at the thores of how to apply Big Data into the enterprise. There are several pathways to start the journey and reach different levels of maturity for the implementation of Big Data. In developing several of these implementations with different companies across the globe, we have created a series of courses that will be presented at TDWI Chicago in May 2013. To give you a perspective, there are courses that target how to build a business case for Big Data to Advanced Analytics on Big Data. As an incentive, TDWI has graciously offered a special discount to attendees and the details are available here

TDWI Chicago Template Krish Krishnan.html

Looking forward to seeing you at the event.

Posted April 3, 2013 8:12 PM
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If you read books on strategy and management as subjects, the end rule always focuses on the term ROI and the time to realize the same. There is nothing wrong in estimating the value of any investment, the market opportunity, risks and time to recover profits, but the situation changes drastically when you apply the same techniques to an organization on all the programs and projects in-house, often resulting in chaotic situations and emotional upheavals.

The main idea behind applying ROI based techniques for any in-house program is to provide management with a roadmap on the value of the investments in technology and the business benefit it will bring about. The one area where we have traditionally struggled to provide a clear and concise point of view is the area of "data", ironically while the same has been classified and touted as an enterprise asset for many years. How does one really apply ROI to data strategy?

The techniques of using data quality and integrated data architectures help in building a business case for data strategy, but does not clearly articulate the ROI as it does not tie the business outcomes to the data strategies used in the organization. In order to measure the ROI on data strategy, we need to employ a combination of
  • projected or predicted ROI from all data programs
  • realized increase in business initiatives
  • increase or decrease in profitability
  • measured customer sentiment

By creating a mashup  of the different pieces, we can create a co-relation on the initiatives of data strategy and the ROI, with a measurement of true impact on the business. This type of value driven mechanism is needed to realize the true ROI on data strategy.

Monetization from the data strategy efforts can be traced with this method and clearly documented along with trends and timelines. This is not a simple exercise and needs to be implemented with acceptable margin of error for the first few iterations till a maturity model can be established.

Once we have this type of a model, every program of data strategy can be tied to a measurable value and you can predict the tangible ROI and the timeline for the realization with a higher degree of confidence. This type of practice exists in many organizations albeit on a tribal scale and it needs to be enabled and empowered to become an enterprise level strategy.

This type of approach uses all the soft costs and the tangible performance results of the business together and hence it is to be treated with utmost security and governance to protect the competitive advantage of the business. Watch for my expanded whitepaper in the next week on this topic.

Posted January 30, 2013 7:56 AM
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The buzz is all about Big Data today in our industry and we all seem to be in a state if awe with this happening. Let us take a step back for a minute and pay attention to the trends that drive business and decision making - it has always been oriented towards competing on products and services since the dawn of time. The advent of web 2.0 and the long tail model combined with the explosion of social media transformed this trend from products to customers.

Businesses started looking at customer sentiments and behaviors closely and started identifying what drives the customer to be loyal to them. Beyond just customer loyalty the trends that have started driving the business is Customer Centricity and associated transformations in business. This is where Big Data plays an important role within enterprises today and the underlying need to integrate and explore the data and insights from the same.

While the buzz from Big Data may stay or die after a period of time, the new trends and directions that it has created for businesses to follow will be the future trend.

Posted November 25, 2012 10:42 AM
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