Understanding Enterprise Data Governance: Part 3

Understanding Enterprise Data Governance: Part 3

This is the third blog post in a series exploring Enterprise Data Governance.  In the first one, we briefly defined transaction data, metadata, master data, reference data, and dimensional data. In the second part, we further explored reference data and its role in data governance solutions. For this installment, we will discuss data governance needs within Financial Services, a highly-regulated industry, and how other industries can benefit from these capabilities.

Most consultants would guess that data privacy is the primary data governance concern for most Financial Services executives.  Data privacy is a critical concern, and cannot be ignored in the normal course of running a stable and profitable Financial Services business.  Maintaining profitability also requires complete, timely, and accurate data to support operational decisions that align with the company strategy, in addition to regulations that require unprecedented levels of transparency and accountability.

The Sarbanes-Oxely Act was passed in 2002 to protect investors from companies’ potentially fraudulent accounting activities. It is well known that this act, which affected all US corporations, legislated individual responsibility, including some personal liability, for key executives in ensuring the accuracy and completeness of financial statements.

The Financial Transparency Act of 2015 further requires that US companies in the Financial sector make the data their financial statements are based upon open and searchable by regulatory bodies, such as the SEC.  There is also a lesser-known provision within the Financial Transparency Act that states that maintenance of reference data supporting financial reporting be made available for audit, including who made the change and when.  It explicitly states that if reporting hierarchies and selection criteria are maintained in spreadsheets, those spreadsheets need to include macros that accurately capture and retain the required fields to support regulatory audits.

Many of the largest Financial Services providers in the US, including American Express, Bank of America, Chase Bank, Wells Fargo, and dozens of others were prepared to meet these regulations since they were using Oracle Data Relationship Management (DRM) to master critical financial reference data.  DRM also has a large global customer base, and it is no small wonder that DRM not only meets and exceeds these stringent regulatory requirements, but also allows its customers to manage reference data across a broad array of enterprise systems, data warehouses, and reporting solutions from a single point of entry and validation.  This is key for an industry full of behemoths that have grown via mergers and acquisitions, often requiring them to manage extreme complexity in mapping their internal management processes to their externally reported line of business financial results with full confidence in both their accuracy and their audit transparency.

For the past decade, DRM has been the most powerful and complete reference data and dimension management solution commercially available, but its use has historically been mostly limited to the upper echelon of industry leaders due in part to both its cost and its marketing focus.  That will change when Oracle releases the next generation of DRM on the Cloud.  An early release was demonstrated at Oracle Open World 2016 as Dimension Management Cloud Services, and we are hopeful to see its production release this year.  The Cloud promises to make this technology, which has the power to manage the most complex business models in existence, available to a broader customer base at an affordable price, with greatly simplified setup procedures.

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