Three Legal Concepts Data Analysts must know to Drive Business Value

We live in a digital world. Every day, every minute, every single second, there is an unprecedented rate of data coming from different sources. As data is the key to technological innovation, organizations across the globe are readily investing in all possible ways to collect data for analysis. Once collected, data analysts are responsible of leveraging the data for the right business use cases that can drive the growth of their organization. After the data collection, and sometimes even before that, the first thing that data analysts do is create a big data strategy so that the organization can move in the right direction, while also weighing in the associated security risks. However, this is not the ideal approach to take.

In order to drive business value with analytics, data analysts should first take into account the legal concepts of data by working jointly with a legal counsel. Doing so will help data analysts to drive economic growth and also mitigate the risks pertaining to data aggregation.

1. Data Ownership

Data ownership calls for a governance policy for the data collected by an organization. Organizations can obtain, share, and utilize data based on the data rights. An organization will agree upon a set of rules that will prohibit data utilization in certain areas, may be internally or externally. Or, organizations will ask for permission to access someone else’s content on any platform. For example, when you open a mobile application or website, you might have noticed that the brand asks you for the rights to access your data. Additionally, before disclosing any data to third-party vendors, organizations should ensure that the data has been granted the s ‘sharing’ rights.

2. Data Protection

Data protection represents the safeguarding data from breaches, hackers, or any other such loss. Organizations should build specific regulations on ‘who’ can access the data. Not only privacy breaches, but organizations should also protect their data from disasters. The best practice to protect data is to create its mirror (a replica of data) or store the data on the cloud. Furthermore, data protection focuses on both ‘data privacy’ and ‘data security.’ Data privacy mainly emphasizes on ‘who’ can access, share, retrieve, and utilize the data. On the other hand, data security prioritizes on ‘secure hardware and software components,’ ‘risk mitigation approaches,’ and ‘post-disaster controls.’

3. Data Sovereignty

Data sovereignty comes into the picture when your organization’s data is residing in some other country, compelling you to follow the privacy regulations of that particular country. If your company requires the data that is residing in some other country, then you will have to first learn from a legal counsel about the laws and rules that are followed by the other country.

To make the most of big data, data analysts should follow the above legal requirements, even before they create the big data strategy. By doing so, companies can mitigate the risks associated with IPR breachesand meet their business objectives effectively.