The Rise of Machine Learning to Manage Dark Data

The Rise of Machine Learning to Manage Dark Data

Dark data is a type of unstructured, untagged and untapped data that has not yet been analysed or processed. With 80% of data being classified as Dark data, there is undoubtedly enough information for companies to leverage to their advantage. Therefore, it is now time to bring light to the unknown gold mine of dark data.

For many businesses, understanding the sheer amount of dark data can be overwhelming and time consuming to manage. Businesses may use excuses like legality issues, workflow disruption or architectural costs as to why it has been reluctant to harness dark data. It may also fear that getting access to dark data can invade valuable time which could be used for other tasks and disrupt employees with new ways of operating. Of course, disruption can be kept to a minimum when implemented correctly with the right tools.

For most companies today, transforming unstructured data into readable assets involves processes that are mostly manual. To create better value, businesses need to automate these processes and free up resources from mundane tasks, and this is where machine learning comes in. Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and accomplish the equivalent of continuously running programmes in a fraction of the time.

Businesses can utilise machine learning to build models that work in the specific business function and industry. In the case of dark data, the process of learning begins with data observations, in order to look for patterns and make better decisions in the future based on previous examples. Typically the system alerts business users to exceptions, and remembers each time they address those exceptions so that it can offer a solution the next time a similar event occurs. If users keep accepting the recommended solution, the system will learn automatically.

Structural changes are required when implementing machine learning, which costs time and money. But it’s worthwhile long term and the business benefits will guarantee a high return on investment.

At a first glance, dark data can appear obscure or unhelpful but when its approached correctly, it can unlock business value and boost the bottom line. The key to uncovering dark data’s secrets lies in the ability to understand the relationships between seemingly unrelated pieces

of information. Machine learning plays a critical role in helping businesses interpret information correctly and reveals a host of patterns or insights that would have otherwise been missed.

In a business climate where data is competitive currency, dark data is valuable as it allows businesses to learn about every aspect of their operations. The larger the dataset, the more accurate the analysis.

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