Infosys-Oracle Blog : Managing uncertainty in deploying a Data Warehouse

Guest post by
Debapratim Dutta, Lead Consultant- Banking and Capital Markets, Oracle Practice, Enterprise Solutions, Infosys Technologies Ltd.

A few weeks back I woke up with the morning newspaper, and was surprised to discover that my sun sign has got changed! The news article explained that according to latest astronomical discovery there is now a 13th zodiac sign, instead of the long held astrological belief that there were only 12. The newly identified constellation which is between Scorpio and Sagittarius is called Ophiuchus. Before I could finish reading the entire news article, a friend of mine called up and sounding highly disappointed, informed me that from now onwards she will be happy to throw the morning newspapers' horoscopes in the bin. Co-incidentally, the day before that, the CRO of a reputed bank in an informal call told me, that from now onwards he will have to throw away many of the risk reports to the bin as most of the sophisticated risk models developed in the past are no longer accepted as valid by the regulators. Sounding equally disappointed as my horoscope savvy friend, the CRO wanted to know whether we can advise some solution to him, as they got to now re-do the entire risk data warehouse to cope up with new regulatory standards announced under Basel III.

Such news on failures of data warehouse projects in financial services institutions are not new. Limited understanding of end use coupled with exponentially increasing degree of uncertainty in the financial services space, makes the traditional approach in data warehouse design unsustainable in the rapidly changing regulatory landscape. Most often complex computational needs are not taken into account during design phase, resulting in ad-hoc delivery mechanisms for results. One primary reason for this is that, traditionally computation has been viewed as external to data warehouse thus making the model inflexible to future needs. Moreover, need for excessive focus to address enormous ETL complexity in mapping sources to enterprise model deviates attention from the ultimate end use.

Thankfully, Oracle has recently come up with an innovative solution to counter flaws in traditional data warehouse design. The recently launched Oracle Financial Services Data Warehouse (OFSDW) readily deploys a pre-built, and end-use proven data model for Financial Services covering key analytical use cases for Risk, Finance, Compliance and Customer Insight. The OFSDW model maps every single attribute to its possible analytical end uses. In doing so, it considerably reduces the initial effort involved during data warehouse development by clearly focusing the exercise of mapping source data on its end use. Additionally, the OFSDW eliminates accuracy and consistency issues with thousands of pre-built data quality checks contextualized to financial services institution analytical end use and also eliminates inconsistencies across ledgers, books and marts through a formal and centralized GL reconciliation process for confident and fully auditable reporting.

Unlike traditional data warehouse design, OFSDW provides an analytical applications infrastructure which comes pre-integrated with 30+ Oracle financial services analytical applications and also can seamlessly work with third party or in house developed applications. The various components of OFSDW like the cube and mart builder, workflow engine, forms builder, statistical library, rules framework etc. provides a technologically advanced framework which can seamlessly adapt to unknown regulatory and business challenges of the future.

So even if the signs of zodiac keep on changing, with Oracle, you can always steer through uncertainty to your desired goals!