6 big data privacy practices every company should adopt in 2018

Although Big Data provides a boon to all of us, it risks millions of unprotected data including those of our private life to the vast world. And problems regarding the security of data has also not been solved or taken forward in the past two years.

Business organisation heads now are threatened on security issues before they think of implementing Big Data analytics in their business models. The threat has now become more enhanced after the Equifax breach, although the data involved here was not Big Data.

So here are some steps that the IT sectors of business organisation can take in their lower levels to improve privacy of Big Data.

  1. Ask your cloud-vendors for privacy – All cloud service companies provide highly encrypted security measures for giving privacy to your data. These vendors can provide for the right measures that you might need for the enterprise. However, it stands as your duty to inquire about it and pay for the services as required. Being in a business enterprise yourself, you might the rule that no service provider will provide the best services unless asked for. Also, ask your team members to check the cloud privacy standards and whether it meets the company’s governing protocols. You can also ask the IT Testing Team to check the security standards of the cloud-vendor. If unsatisfied, feel free to move on to a better vendor. Also, make sure, that the security protocols are frequently checked and upgraded atleast once in a year.

 

  1. Utilise private clouds – Most vendors will provide private cloud services. However, these plans are expensive than the multiple used public cloud. But using this private service will help to set apart your company data from other data.

 

  1. Make the data Anonymous – This step will help you to not only protect each of your client’s data individually but also analyse them for recent trends of the market. The process can be done by many ways – one by encrypting the data for personal identification; second by grouping the similar data values in to a single average data (like calculating gross annual income) which can be further utilised in bigger data analysis procedures; or by data redaction or data masking.

 

  1. Ensure that all Departments of the Enterprise follow the Privacy standards– For a large organisation, multiple departments are using various sets of data simultaneously. To follow all such data would require a huge security department which is surely a waste. However, you can ensure that each department, especially the bigger ones, follow the rules and not change the data in to something that does not the standards. Ask external auditors to frequently check the privacy standards of these bigger departments and verify whether it complies to the security protocol norms. Non-compliance should be immediately resolved.

 

  1. Follow the GDPR – If you are North American multinational company, make sure than your business follows line by line the GDPR (General Data Protection Regulation) set down by the European Union which is affirmed to be effective from May 2018. Not following these protection rules will result in a hefty fine for the organisation. Even if your enterprise does not branch in to European countries, start practising the rules, as surely other governments will follow these steps.

 

  1. Perform social engineering inspections – Though it may be hard to hear, but inappropriate sharing of critical data by the employees to the outside world has always been a factor in every business enterprise. And hence the reason to perform a social inspection along with the inspection of our business model atleast once a year. This inspection will look for phishing attacks, threatening phone calls and deceptive moves which may be performed by an employee of your enterprise also.
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BI Consultant

DataFactZ is a professional services company that provides consulting and implementation expertise to solve the complex data issues facing many organizations in the modern business environment. As a highly specialized system and data integration company, we are uniquely focused on solving complex data issues in the data warehousing and business intelligence markets.

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