The Story of Data — Privacy By Design
By: Manoj Kukreja
Tags: Privacy, Data, Data Science, Artificial Intelligence, AWS

Discuss the need for adopting frameworks like Privacy By Design very early in your data management life cycle

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Every byte of data has a story to tell. The question is whether the story is being narrated accurately and securely. Usually, we focus sharply on the trends around data with a goal of revenue acceleration but commonly forget about the vulnerabilities caused due to bad data management.

Data possesses immense power, but immense power comes with increased responsibility. In today’s world collecting, analyzing and build prediction models is simply not enough. I keep reminding my students that we are in a generation where the requirements for data security have perhaps surpassed the need for data correctness. Hence the need for Privacy By Design is greater than ever.

Before we discuss Privacy By Design lets understand some issues surrounding data security and privacy.

Security — Role of Data Processors & Data Controllers

A few years ago just building a Data Lake was a quantum leap for many organizations. For security conscious organizations security of the Data Lake was simply limited to enabling Kerberos for identity management. We rarely talked about security of data-at-rest or data-in-motion. Not any more….

In today’s world the role of data processors and data controllers has been redefined. Handling data securely whether it is at rest or in transit is no more a option. On top of that the organizations are legally bound to notify the involved parties as soon as any data breach has been detected.

Speed of Data

Until recently businesses have focused on looking at data over long stretches of time, made possible by Big Data. With the advent of Internet of Things (IoT) analyzing real-time data has gained immense importance. It is very common these days to have devices in our homes that collect personal data and transmit it to external locations for either monitoring or analytical purposes. In many cases the the poor consumer is finding it difficult to balance the benefits they get from surrendering their personal data against the risk involved with providing them. A right balance needs to be met.

Privacy By Design

We are in times where history is being made on a daily basis. While giants like Facebook, Google and others are looking at innovative ways to collect, handle, use and share data the legislators are drafting and enforcing new regulations around data privacy and ownership. Regulations like the European GDPR attempts to define the legal accountability of data controllers and data processors. The regulation puts greater focus on data governance polices around personal data portability, retention and destruction.

What is Privacy by Design?

Integrate privacy issues from the beginning and throughout you development cycle.

The same approach should apply to services offered as well as internal processes. The theory behind this approach is that privacy cannot be solely enforced by legislation alone.

Privacy by Design is based on 7 foundational principles, as developed by Ann Cavoukian and formalized in a joint report with Information and Privacy Commissioner of Ontario.

More than ever IT companies are trying to help customers come up with the correct blend of data innovation and data governance in a security-conscious world. As the use of machine learning and artificial intelligence gains strength we need to help our customers adopt frameworks like Privacy by Design to make their future data roadmaps simpler, secure as well as cost-effective.

I hope this article was helpful in spreading the news regarding the adoption of Privacy By Design. Topics like these are covered as part of the Big Data Hadoop, Spark & Kafka course offered by Datafence Cloud Academy. The course is taught online by myself on weekends.