Undoubtedly, the digital space today is driven by data quality and quantity. With this comes the challenge of protecting it and turning it into facts and insights. Here is how to make it productive and easy to store and secure.
Following a data strategy might not seem important to many, but it can help businesses effectively protect sensitive data, mine it for insights, and provide a roadmap for storage.
With the growing data and communication breaches, there is a need to create awareness about complying with data regulations. In fact, only less than half of the people are aware what encryption is, or how their data should be protected.
According to a recent report released by Gemalto – the international digital security company, two out of three companies globally are unable to analyse all the data they collect and only half the companies know where all their sensitive data is stored.
Further, organisations admit that they don’t carry out all the procedures in line with data protection laws such as the General Data Protection Regulation (GDPR).
The research found that business’ ability to analyse the data they collect varies worldwide, with India and Australia being the best at using the data they collect. “If businesses can’t analyse all of the data they collect, they can’t understand the value of it – and that means they won’t know how to apply the appropriate security controls to that data,” says Jason Hart, vice president and CTO for data protection at Gemalto.
Thus, aiming to provide a platform for storage optimisation for edge devices and the ability to run bigger data analysis, the software company HarperDB recently launched its geographical data analysis and storage with features designed to allow real-time geo-analysis.
As a result, companies tackling complex IoT (Internet of Things) projects can achieve a more intelligent edge without incurring further storage or hardware costs.
Similarly, softwares like Apache Hadoop have been acting as big data frameworks. They allow distributed processing of large data set across clusters of computers to make data processing faster and flexible.
Qubole Data is another programme with its open-source engines, optimised for cloud. It provides actionable alerts, insights, and recommendations to optimise reliability and performance.
To accomplish big data tasks with less code, companies can switch to programming languages like HPCC. These languages deliver on a single platform and a single programming language for data processing. Further, they can also be used for complex data processing on a Thor cluster.
For data clean-up and transformation to other formats, use applications like OpenRefine, or Rapidminer for text mining and predictive analytics.
Apart from processing and storing, it is also important to encrypt data. It is not enough to just delete information from a computing device. Often, the deleted data still exists on disk and can be recovered. The only way to ensure that the deleted data is gone forever is to overwrite it.
Tools like VeraCrypt and CertainSafe amongst many others are easy to use and add encrypted passwords to data.
Go for platforms where you can store and share documents and files without exposing them to third-party sources. Businesses can even collaborate and communicate with colleagues through these systems, with all correspondence encrypted.