Data Management – The Challenges

Does your company suffer the challenges from data silos? Dessa Glasser, Principal with the Financial Risk Group, who assists Virtual Clarity on data solutions as an Associate, discusses the challenges of data management in our second post for our blog series.

In our previous blog, we talked about the need for companies to get a handle on their data management. This is tough, but necessary. As companies develop – as they merge and grow and as more data becomes available to them in multiple forms – data silos occur, making it difficult for a ‘single truth’ of data to emerge. Systems and data are available to all , but often behavior among teams are different, including the ‘context’ in which the data is used. Groups have gathered and enhanced their own data to support their business, making it difficult to reconcile and converge to a single source for business critical data.

This complication is magnified because:

  • New technology brings in large amounts of data – both structured and unstructured
  • Each source has its own glossary of terms, definitions, metadata, and business rules
  • Unstructured data often needs tagging to structured data to assist firms in analytics
  • Structured and unstructured data require metadata to interpret the data and its context

As Dessa Glasser notes, “The problem is not getting the data, the problem is processing, interpreting and understanding the data.”

Companies can also be hindered by the ‘do it yourself’ mentality of their teams, whereby individuals who want systems implemented immediately will often construct a process and data themselves, rather than waiting for IT to deliver it, which either takes time or may not be not available on a timely basis.

 These cross-over efforts undermine a firm’s ability to effectively use the data and often leads to:

  • Data sources being available in multiple forms – both internal and external
  • The costly and manual reconciliation of incorrect data and difficulty aggregating data
  • The inability to generate business insights from the data – more time is spent processing, and reconciling the data, rather than analyzing it

Meanwhile, clients are demanding a holistic view of the services they’re buying into, and management and regulators, when they ask for data, want to know the full relationship with clients across the firm and a holistic view of all aggregated risk positions, which is hard to pull together from numerous teams who work with and may interpret the data differently. Companies must present a cohesive front, regardless of each team’s different procedures or context in which the data is used.

All of the above are prime examples of why the governance and management of data is essential. The end goal is one central, logical, authoritative source for all critical data for a company. It is important to treat data as a business asset and ensure the timely delivery of both well-defined data and metadata to the firm’s applications and business users. This can be done by developing a typical data warehouse to serve up the data, which often can take years to build. However, this can also be facilitated more quickly by leveraging advances in technologies, such as the cloud, data access and management tools, and designing a Data as a Service (DaaS) solution within a firm.

So, how to go about it?

Tune in next month to blog 3 where we’ll discuss.

Dessa Glasser is a Principal with the Financial Risk Group, and an independent board member of Oppenheimer & Company, who assists Virtual Clarity, Ltd. on data solutions as an Associate. 

Questions? Comments? Talk to us on Twitter @FRGRisk

Related: