Today business activities are gradually going online, and marketing and CRM are the buzzwords of business today. Online financial transactions, customer interaction with companies (orders, emails, and invoices), social media communication, sensor data from various machines, and many other activities that people do in routine life, are contributing to the current explosion of data. However, one major aspect of such explosion is something called Dark Data, let’s find out more about it.
Definition of Dark Data
Data that an enterprise collects over a long period of time may lose its relevancy as it will become out-of-date. Its utilization in current date is questionable, data may become obsolete and irrelevant to current activities. Dark Data may contain some crucial and confidential data, to be refined for profit earning opportunities or strategic decision making.
High frequency of interactions between enterprises, customers, employees and people has resulted in the generation of the so known Big Data and secondarily Dark Data. Dark Data exists within organizations and it represents a big deal, to manage it we must understand various related aspects.
- Dark data is growing rapidly, it doubles every 10-12 months raising the need for larger and efficient storage structures.
- The unstructured nature of this data in the form of images, videos, animations, text, and docs make it difficult to classify and convert it into a useful form.
- Innumerable sources generated by social interactions, user clicks, consumer interaction, financial transactions, weather forecasting, stock exchanges, and many others sources that make it difficult to organize.
Issues with Dark Data
- Organizations have to spend a fortune in storing this unanalyzed and unprocessed data with some chance that they might need it in the future. It would be better to process, analyze, compress and backup Dark Data to reduce its volume.
- It may have legacy data, which may prove to be fatal for the company if it lands in wrong hands. It may be related to old business deals, financial transactions, technical details of products, organizational plans and strategies, customer communications and details of earlier employees.
There must be cost effective and efficient processes to manage and organize dark data so access to this legacy data, stored for years, will extract real business value from this huge and unused repository. At this age, when organizations are awakening and understanding the need of newer technologies and solutions, Dark Data must be a matter not to ignore.