Understanding the concept of Dark Data

1. Understanding the concept of Dark Data

2. We are living in times when every day we are introduced to a discovery. There is a new technology to adopt and a new concept to learn. One such concept is Dark Data. The term hasn’t been there for a very long time so obviously not many know about it. Firms involved in business activities like legal process outsourcing use it a lot. Let’s learn more about the concept in detail. What is Dark Data? Dark Data refers to Information that organizations like top legal process outsourcing companies in India collect and store for the purpose of their regular business activities and generally fail to use for any other purposes. In simpler words, it is forgotten data that once might have been used for general work purposes and left unutilized afterward. Organizations often forget that they still have it in their data ecosystem. Now, this sort of data is everywhere in the form of employee records, attachments, surveillance records, presentations, emails, survey data, and more.

4. How do organizations end up with dark data? Every year organizations including top legal process outsourcing companies in India generate tons of data that is beyond their capability to analyze. It is said that half of this collected data goes unanalyzed and the percentage is only rising. It is believed that every minute a person creates 1.7 MB of data for himself. There is a population of 7.3 billion people on this planet. Now, imagine, how much data is created every minute every single day. Even though companies have a pre-defined data model, almost 65% of data remains unstructured and the percentage is only expected to rise coming years.

5. How can organizations including top outsourcing companies in India discover dark data in their system? There are mainly 6 factors via which any firm can evaluate its data and identity • Quality Unstructured data means that there are high chances that are some double entries, incorrect patterns, and missing details in the data. This suggests poor data quality which ultimately is of no use as incomplete info only gives inaccurate insights. • Redundancy Copies of data are no good. Why keep two when one is enough? It can be detected using the ML technique. It can help you get rid of redundant data.

7. 3. Low popularity Data which has a low trusted source or is not widely used is good for nothing. So, periodic evaluations of whether any department or system is using them are necessary to eliminate the possibility of stacking dark data. 4. Staleness Anything kept aside and not used for a very long time becomes stale. The same is the case with data. Analyze your data and see when was it last modified.

8. How can it be handled? One thing you must note is that dark data does not mean bad data. It is data that’s not been used for a long time. The best legal process outsourcing companies in India can handle it by figuring out a way to manage it more efficiently.