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Data Quality: Are you a brick inspector?

Alex Olson
5/31/16 7:30 AM

In May 1980, a Barnard College student died in New York City due to a piece of terra cotta falling from a building. This terrible situation caused Local Law 10 to be passed in New York City, which was further strengthened by Local Law 11 in 1998 after a similar tragedy. These laws Big Data Qualityrequire the façade of each building to be inspected to ensure that the bricks are firmly connected to the structure.

Why are we talking about bricks? As I was walking to one of my client meetings in New York, I observed this process occurring. Scaffolding was erected, individuals were looking at individual bricks, and small fixes were being made. The people on the sidewalks were affected due to the scaffolding in place. I am not a building engineer, but I asked myself, "Is there a better way?" My mind then proceeded to my client meeting and data quality. Were the clients like the brick inspector?  Were they rebuilding the scaffolding, looking at the façade instead of the root causes? Plodding through records manually instead of using tools to find the problem?

Unfortunately, the similarities between data quality in the industries we serve and the brick inspector are significant. We believe that there is a better way to optimize your quality. Take a look at this table.

The Brick Inspector Approach

The Modern Approach

Reactive: Initiated due to tragedy striking – customer or regulatory driven

Proactive: Identifying and preventing potential problems

Set-up and tear down (scaffolding)

Architected as a foundational piece of the operation

Periodic when regulators or customers ask

Consistent and continual – operationalized

Throw people at the problem – similar to finding a needle in a haystack

Leverage technology to find the exceptions

Treatment: Fix the façade

Cure: Understand the root causes and resolve them at the source

We believe the modern approach exists and is available today. As discussed in other blogs, data diagnostics  are available to use technology to find the exceptions. Like a tool that can scan a building to find structural weaknesses, data diagnostics can find the issues with your data.

But discovering your data issues is the first step. Dig deeper by using data management maturity models to understand how you are treating data. You can uncover what is occurring below the surface instead of inspecting the façade and reacting after it's too late.

Please contact me to understand further how to move from the Brick Inspector to a modern, technology enabled approach.

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