Data privacy and security abstract

Managing data privacy in the enterprise

Managing data privacy in the enterprise

The growing use of analytics and big data has created large data privacy concerns. Everyone, especially the federal government, has taken notice of the events known as Big Data. Back in 2012, nine companies in the data broker industry were the first to be issued orders from the Federal Trade Commission.

The FTC required them to hand over all information regarding their usage and consumer data collection practices. The federal government’s actions meant there were significant concerns regarding consumer privacy and its implications if misused.

What are significant data privacy concerns?

The Federal Trade Commission’s action first targeted data brokers. These are companies that collect and analyze consumer behavior data. What they accumulate is then sold to other companies wanting to step up their marketing and sales efforts.

Now besides the data brokers, there are other industries, that use and collect big data. They are:

  • Biotechnology
  • Consumer goods
  • Financial services
  • Healthcare
  • Information Technology
  • Manufacturing
  • Pharmaceuticals
  • Professional services
  • Technology

What draws critical privacy concerns and gets noticed by the federal government is the quality or accuracy of the data gathered. For example, how accurate is personal information acquired from a website or a social media account? Should that information be used to screen or rank job applications, or increase the price of medical insurance? Will the information gathered, which could negatively impact them, keep the individual from getting a job or paying higher rates for insurance?

Why Should You Use Big Data?

In the past, data warehousing had a different function. Today, though, Big data performs analytics on almost any format and data file type. Another crucial benefit of big data is that it relies heavily on a virtualization architecture. It does not require the server to data storage relationship it once did. That means big data’s single global resource relies on what gets extracted from large content stores.

What are some enterprise best practices for managing data privacy?

Due to its continued growth and change, enterprise data best practices continue evolving. With the government strictly keeping an eye on data privacy, what have we learned so far, will help you when managing data privacy as innovation moves forward.

If you want your big-data to be cost-effective; the first step is becoming highly competent in managing and procuring cloud services. What you will find with that commitment is added flexibility the cloud offers.

The next best practice is implementing converged storage. Converged storage has proven to be more efficient. The likelihood of errors which influence your data accuracy and quality gets dramatically reduced. A crucial benefit with converged storage is data de-duplication. De-duplication is the elimination of duplicate or redundant information, especially in computer data.

Another best practice is to sanitize your data correctly. Sanitizing your data helps you avoid many privacy issues. At the earliest possible touch points, you must apply:

  1. filtering
  2. cleansing
  3. pruning
  4. conforming
  5. matching
  6. joining
  7. diagnosing

Also, do remember, all of your data sources need linking and readily available for reference. The purpose of this is should a data element get questioned; the link traces it back to its original source.

Finally, your best safety net for personal data is the accuracy. One of the most heated privacy concerns is the idea of obtaining consent or permission to collect and use personal data. Being transparent with consumers to review information collected about them is typically not offered.

We would encourage you to invite and proactively promote a process for consumers to access and correct their information. That practice would allow them to have their data removed and purged, giving them back control of their personal and sensitive data.