Shining the Light on Dark Data to Generate Impactful Business Insights

Sep 27, 2017

healthcare retail

Businesses rely on various data sources to gather information for making intelligent business decisions. The practice of recording structured data for further market intelligence uses is relatively new, lacking large volumes of data to derive an accurate insight. However, CIOs, business leaders, and data scientists are looking beyond the available data sources towards the deep web to explore an astonishing amount of raw data to unearth valuable customer, business, and operational insights. With advanced technologies, organizations can analyze data from sources such as images, drawings, handwritten notes, satellite imaging, social media sentiments, and customer interaction, which were previously impossible.

What Types of Insights Can Dark Data Yield?

Organizations can harness the power of dark data to dive deep into the root of the problem to generate relevant insights, identify patterns, and relationships, that usually go unnoticed by traditional BI and analytics tools. For instance, one popular fashion retailer used dark analytics to identify customer churn factors by studying how and when a customer dropped off. The brand could then predict the reasons for such customer churn, and craft more targeted and relevant re-engagement strategies as opposed to the usual “We will miss you!” e-mails.

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How can Brands Make Better use of Dark Data?

To process and analyze dark data, brands need to account for all unused data, give it structure, and integrate it into existing data processes. For instance, tracking social shares is not an easy task. However, brands can give such a process structure by adding a share button with UTM embedded to track such dark shares. Organizations will have to update their legacy systems to enhance their ability to see and analyze dark data.

If you’ve got any queries on dark data and how your organization can use analytics to gather meaningful insights, request for more information.

Pitfalls in Mining Dark Data

1. Using dark data such as patient records, credit card information, and other confidential account data can expose an organization to legal and regulatory risks

2. Businesses will have to dwell through proprietary or sensitive business information, the disclosure of such information could compromise important business activities and relationships

3. The user might lack the tool or solution to analyze unknown sources of intelligence

Ready to Harness Game-Changing Insights?

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