Dark data often holds huge potential and may contain secret information that could prove to be transformational for the organization. With the right tools and techniques, organizations can lead the competition by tapping unseen insights from dark data and achieve greater heights. Revealing the data conundrum, IDC estimates that by 2025, there will be 175 zettabytes of data globally; out of which 80% being unstructured and 90% of unstructured data never being analyzed (quotes Forbes). Isn’t that a startling number to dig in?
Beginning by understanding what dark data refers to, related effective data management strategies, and how can organizations leverage it for their growth- Let’s explore now.
Dark Data – A Hidden Gem
You might be wondering what dark data is and how it can be useful for organizations.
Well, organizations collect huge amounts of data, or big data, from a variety of sources, including social media, emails, customer feedback forms, sensor data, and more. While a lot of data is used for analysis and decision making a huge portion of the data collected and stored by organizations is not used for any purpose.
This unused data is called dark data or ‘data that lies in the shadows’, which has huge potential but is not actively used in decision-making processes.
There can also be various reasons why organizations store dark data such as for compliance purposes or for record keeping. Some simply store them believing they might need the data in future for better insights or if they have better technology.
But organizations need to understand that poor data management can be a costly affair and even compromise the privacy and security of sensitive information. This is why it becomes important for them to analyze how valuable their dark data is and must balance the value of dark data with cost and hazards associated with it.
Value of Dark Data for Organizations
If tapped properly, dark data possesses immense value for organizations. This data can offer never seen before insights and business intelligence which otherwise might go unnoticed.
Analyzing dark data enables businesses to understand their customers, operations, and latest trends in market in a better way. Organizations can make the best decisions for their business to enhance their operations and increase productivity. This helps them tap into the lost opportunities that were previously uncovered with unknown trends and patterns.
Say, for example, organizations can analyze dark data to understand their customer preferences, pain points, or purchasing patterns, which would improve customer satisfaction.
Where to Access Dark Data?
Though the benefits of dark data are transformative, it can be difficult for organizations to find it on time. They are often hidden inside humongous amounts of datasets and are not easily available. But with the following methods, data science professionals can easily identify and trace them.
It includes understanding the structure, content, and quality of data to determine their characteristics and potential value. This is done to highlight overlooked datasets that can be useful in the future.
Data professionals need to use advanced data discovery tools to scan big data and detect patterns, anomalies, or relationships.
Using targeted keyword or phrase searches across systems and repositories can help find dark data sets.
Organizing data based on various factors like their value, sensitivity, retention policies, etc., will help businesses detect repetitive and outdated data. They can be then archived or deleted as required.
Regularly auditing the access logs, system logs, and backup files can also help find untapped data that can be useful for organizations.
Organizations must understand that discovering dark data is not a one-time task but requires continuous monitoring, evaluation, and data governance for maximum benefit.
What Leads to Dark Data?
There are various reasons that lead to the creation of dark data, such as:
Unstructured data, such as that acquired through emails, papers, or social media posts, is not so easy to analyze or use properly and becomes dark data.
When organizations lack data management policies and procedures data are collected or stored without clear goals and thus are lost.
Data silos refer to data isolation within an organization where different departments are busy collecting, storing, and managing their own data which makes data exchange difficult.
Organizations that do not upgrade and use outdated technologies that are incompatible with current systems, which makes accessing data on the latest devices difficult.
Dark Data- An Asset for Businesses?
To fully exploit the potential of dark data, organizations must start by defining clear business objectives. It is essential to know what aim you want to achieve like improving customer satisfaction or something else, then prioritize relevant data sources, maybe the customer feedback.
For this, right tools are also important such as Natural Language Processing (NLP) can help extract insights from unstructured text and data mining could be used to find trends in large datasets.
Apart from these, cross-functional teams should also collaborate including IT, data science, or business teams to ensure data is analyzed and aligned with the overall organizational goals. Organizations must implement a robust data governance framework to encourage ethical use of data and enhance security and privacy of their data.
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