Locking Down Your Data
  • 8th May, 2018

Locking Down Your Data

By Kingston Coker

Data breaches seem to occur every day and everywhere. (Dare we talk about Facebook and Cambridge Analytica?) Nowadays, almost every mobile application starts up with the alert, “We have updated our privacy policy. Please take a second to review it”. With so many applications tightening up their data privacy policies, it is essential that data scientists do the same.

Data scientists work with large data sets from various companies and organisations. The potential for things to go wrong is not insignificant. Here are five tips that get me by. 

  1. Only take the data you need: This helps reduce the amount of data that could fall into the wrong hands should there be a security breach on your system. 
  2. Encrypt your data: This is typically a low-cost way to add an extra layer of protection.
  3. Use secure sharing services: This is particularly helpful for very large data sets. The S3 bucket on Amazon Web Services (AWS) for example, implements a secure file transfer protocol (SFTP) server with authentication protocols to restrict access.
  4. Be obsessive about protecting customer data: One colleague of mine formats his computer after every project. While that may be an extreme measure, it does help to scrub the system clean of any lingering bugs that may compromise customer data in the future.
  5. Be careful of free wifi: Nothing is really free. Connecting to free wi-fi makes your computer prone to hacks. Try to use (but not reuse) complex passwords and keep track of them with a password manager. 

While following these steps will not keep you safe from every danger out there, they should help to minimise the risk of breaches to your data.

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About Author

Kingston studied Computer Science and prior to joining Ixio, facilitated lectures and discussion sessions at tertiary level during which time, he also developed a point of sale system for the institution. At Ixio Analytics, Kingston uses his extensive software development skills to engineer smart data modelling solutions for data driven decisions amongst businesses. Languages under his belt include Java, C#, Python and PHP. He is passionate about the problem solving process when tackling practical problems and bringing his solutions to life. He is currently taking time off to complete a Masters in Big Data and Cybersecurity at Loughborough University in the UK.