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New Frontiers in Business Intelligence

Nari Kannan

Fixing the Fifth Root Cause of Bad Data Quality - Errors in the BI Reporting Logic

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Some time ago I wrote another blog entry - Five Root Causes of Bad Data Quality in Business Intelligence.

The fifth root cause of bad data quality is errors in the BI reporting logic.

In the ideal world, enterprises have ONE SINGLE BI ARCHITECT and PROGRAMMER who has been there for ages, knows the business inside out, knows the data-reporting requirements inside out, has designed the data warehouse from scratch, and has designed the reports themselves all on his own, satisfying perfectly the needs of his BI users.

But we are not in the ideal world, are we?

Just ask people developing BI reports in a company what the definition of a customer or a client is. From every one of those, you will get a different answer, and some may even have more than one definition.

Many times, bad data quality may not be in the data itself, but how it is interpreted and reported.

There are so many ways that data can be interpreted and reported by different people within the company that quite often what is perceived as bad data quality may be bad data interpretations.

Typically, BI reporting evolves over a long period of time, maybe 10+ years in some instances. The original business groups and the original IT folks that designed the data warehouse have moved on and a second or third generation of business owners and programmers may be in place now. Do they understand how the data was structured, has evolved, and how it is interpreted now?

This problem can be minimized in a number of ways:

a. Extensive Documentation: Archiving and preserving all old discussions and designs leading up to the present day data warehouse is crucial for passing on somewhat precise definitions of what was done before.

b. Data and Information Dictionaries: A centralized data and information dictionary is crucial for maintaining a common understanding among all stakeholders, especially when they are changing over a period of time.

c. Periodic Review of Terms, Data and Information Directories: Do we still mean what we meant something to mean some time ago?  Are we all on the same page with respect to what the data means?

Bad data quality may be a false negative when the data is correct but our definitions for BI reporting are wrong. Chasing our own tails can be avoided if this can be explored and eliminated by chasing after bad data quality and fixing it.

Perception is strong and sight weak. In strategy, it is important to see distant things as if they were close and to take a distanced view of close things - Anonymous

Nari Kannan's blog explores how new approaches to business intelligence can help organizations improve the performance of business processes--whether these processes are creative or operational, internally-focused or customer-facing, intra-departmental or across functions.

Nari Kannan

Nari Kannan started and serves as the CEO of appsparq, a Mobile Applications development company based in Louisville, KY with offices in Singapore and India. Nari has over two decades of experience in computer systems development, translating product and service strategy into meaningful technology solutions, and both people and product development. Prior to this, he has served as both Chief Technology Officer and Vice President- Engineering in six successful startups, two of which he co-founded. He has proven experience in building companies, engineering teams, and software solutions from scratch in the United States and India. Prior to this, Nari started Ajira Technologies, Inc., in Pleasanton, CA, where he served as Chief Executive Officer for more than six years. While at Ajira, Nari was instrumental in developing service process management solutions that modeled, monitored, and analyzed business processes, initially targeting the Business Process Outsourcing (BPO), Telecom, and Banking verticals in India, and Finance, Insurance, and Healthcare verticals in the United States. Prior to this, he served as VP-Engineering at Ensenda, an ASP for local delivery services. He also served variously as Chief Technology Officer or VP-Engineering at other Bay-Area venture funded startups such as Kadiri and Ensera. He began his career at Digital Equipment Corporation as a Senior Software Engineer. Nari has a long involvement with Customer Support and other customer facing processes. At Digital Equipment Corporation he was involved with their 1800 person customer support center in Colorado Springs, Colorado. He was tasked with coming up with innovative tools to help customer support people do their jobs better. He holds a U.S patent for a software invention that automatically redirected email requests for customer support to the right group by digesting the contents of the request and guessing at which software or hardware support group is best equipped to handle it. At Ensera, he led a 45 person team in developing an internet based ASP service for handling auto insurance claims, coordinating information flow between end-customers, Insurance companies, Repair shops and Parts suppliers. Ensera was acquired by Mitchell Corporation in San Diego. Nari holds a B.S. degree in Physics from Loyola College, and an M.B.A degree from the University of Madras in Madras, India. He graduated with a M.S. degree in Computer Science from the University of Massachusetts at Amherst in 1985. Contact Information: Nari Kannan. Email: nari@appsparq.com Mobile: 925 353 0197. Website: www.appsparq.com View more .


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