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How will GDPR complicate data collection?

Maggie Kimberl
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The GDPR provides for the privacy of EU citizens regardless of where in the world their data is stored and used, so today’s CDO will need to have the ability to manage data collection, storage, and usage accordingly. Maggie Kimberl explains how this regulation complicates data collection.

Every day through our smartphones, tablets, and computers, we create more than 250 million terabytes of new data. Social media platforms, web traffic, and online reviews are just a piece of the data recorded each day. Businesses also record demographics for consumers and their own employees, monitor operations, and track their finances digitally.

This amounts to large volumes of data being generated that has to be stored in a meaningful and uniform way for careful analysis at a later time. All of this information is stored, processed, and analyzed by a growing corp of chief data officers (CDOs), the newest seat in the C-suite.

What do we do with all this data?

For years, massive amounts of data were collected but nothing was really done with it. It’s difficult to search through all that data, especially if it’s not collected in a way that makes analysis simple. Data must be uniform for a 1:1 analysis, and it has to be collected in a timely manner to make analysis actionable. Thanks to advances in AI and computing power as well as advances in how data is input and stored, companies are able to analyze that data to gain actionable business intelligence.

While computers and software collect massive amounts of data, not all data is created equally. In order for businesses to benefit from large datasets, they must be collected in a timely manner and contain data that is well suited to analysis and comparison. This takes careful planning and strategy. Once data is collected, it must be kept secure and analyzed for maximum effectiveness.

Businesses use data analytics to guide their decision-making processes. Descriptive analytics tell about current trends, while predictive analysis can extend these models to predict where trends will lead in the future. Prescriptive analytics can take things a step further, by analyzing and recommending the best steps to streamline production or maximize resources.

How will GDPR complicate data collection?

There is also a new layer of difficulty for CDOs – the GDPR. Not only do CDOs need to know how to manage and analyze data these days, they also need to know where that data is coming from and how to protect it. The GDPR provides for the privacy of EU citizens regardless of where in the world their data is stored and used, so today’s CDO will need to have the ability to manage data collection, storage, and usage accordingly.

Data can be stripped of identifying information in order to make it less desirable to hackers while also keeping in line with GDPR requirements. Any data that contains identifying information about EU residents needs to be stored in such a way that it can easily be retrieved and deleted upon request. This presents a major challenge for CDOs.

SEE ALSO: Developing in the cloud in the age of GDPR

Who are some notable CDOs?

When Capital One appointed their first CDO in 2002, the job was a rare one, but CDOs are becoming more common. In addition to finance, many other industries are turning to CDOs to manage their data and analytics. Big cities like Chicago and New York are turning to CDOs to manage city data as well, and around the world companies and governments alike are harnessing the power of big data.

Notable CDOs from the United States include:

  • Cathryne Clay Doss, appointed by Capital One in 2002, was one of the first CDOs in the world. She is currently the Multifamily Business Data Officer at Fannie Mae.
  • Usama Fayyad, appointed by Yahoo in 2004, created Yahoo’s user targeting through big data analysis. He is currently the CEO of Open Insights.
  • Steven Hirsch, appointed by NYSE Euronext in 2007, helped develop technology that analyzes big data quickly. He is currently the CDO of NYSE Intercontinental Exchange Group.

What’s the point of analyzing big data?

Big data analysis can help companies with actionable data intelligence. It gives artificial intelligence the knowledge base necessary to make informed decisions, which is already having big payoffs in things like customer service and predictive texts.

Big data that is well organized and correctly analyzed can help companies save money, conclude research faster, jump-start new projects, and more. It takes the right chief data officer to make all those things happen.

Learn more about the growing demand for CDOs here.


Maggie Kimberl

Maggie Kimberl is a freelance writer and lover of infographics based in Louisville, Kentucky, USA.

You can find her on LinkedIn and Twitter.

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