Dark data is the information the organization collects, processes, and stores with regular business activities. Still, they failed to use it for other reasons like, for example, business relationships or analytics. Many stores secure the information, which may have a considerable risk and cost more than required.
Dark data include Financial information, transactions, emails from downloaded attachments, CCTV camera footage, past employee records, and more. The data referred to something left behind by general processes that are now unutilized, unused, and unknown. This data might be spread across all organization areas, meaning it can be anywhere.
Different organizations have different cases. Some of them are outdated or insufficient to have any value, and in another case, the dark data was in a form that is not accessible with the organization’s tools. Since many businesses collect and store dark data over some time, it might be unstructured, outdated, and unguarded. So, there are chances of risk if the data is collected in the past and the company is not aware.
The data breach issue can occur by cyber criminals will average this sensitive data for their malicious intent. So, it is essential to keep this data protected. But apart from this, it can be used to explore new revenue source opportunities and decrease the amount of expenses.
If you want to address this data, you can use different technologies, like artificial intelligence and machine learning, to manage and protect the information and use it later for some insights.
Some artificial intelligence tools for processing dark data are Google Cloud Vision and Microsoft Cognitive Services. A deeper understanding of this data involves the knowledge of NLP (Natural language processing), Python, Java, and more. You can hire a professional for your organization to protect or use the dark data.
