Unveiling the Power of Dark Data in Strategic Decision-Making

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Read more about author Nahla Davies.

If you’ve never heard of dark data, you’re not alone. Setting aside the ominous name, dark data isn’t something that is inherently bad – although, in practice, it usually does end up this way.

Dark data is usually unstructured data, though it can also be semi-structured or structured data that a business collects and stores but does not use.

This presents a clear inefficiency and a wasted opportunity: With this type of data, storage costs still apply, but the potential benefits that analysis can bring are left out, which is a clear case of opportunity cost. This usually overlooked treasure-trove of data is also a vulnerability in terms of both security and compliance.

Dark data isn’t an edge case. This is a ubiquitous problem, with research from storage provider Seagate indicating that a staggering 68% of data falls into this category.

However, everything isn’t as dark as you might have come to believe. While this is a far-reaching issue, there are ways to leverage this hidden resource, turning a liability into an asset. Join us as we take a closer look at the issue and shine a light on dark data.

What Is Dark Data and Why Is It Overlooked?

To begin, we need to understand what exactly dark data is and the function it serves.

Imagine data generated daily from various sources – whether server log files, unused customer information, or unstructured social media data. This data is often set aside, deemed too complex, irrelevant, or simply forgotten.

But why does this data remain in the dark? There are a few key reasons:

  • Perceived irrelevance: Often, organizations view this data as outdated or redundant.
  • Complexity and format limitations: The unstructured nature of dark data can make it challenging to process with traditional tools.
  • Lack of awareness: Many businesses don’t even realize the existence of this data.
  • Redundant, obsolete, or trivial (ROT) data: The accumulation of unnecessary or outdated information, often due to multiple copies of the same data, contributes significantly to the dark data phenomenon
  • Incomplete data integration: Ineffective integration processes can create data gaps and inconsistencies, leaving some datasets isolated or inaccessible.

While these issues can be ameliorated, the direction that the tech landscape is going in all but guarantees that dark data will always be an issue to some degree. Whenever we integrate new innovations, such as cloud automation, we open up a can of worms, as entirely new categories of data arise – most of which carry all the risks of of dark data and will be underutilized.

This includes expenses-related data that often gets lost in the shuffle, making it hard for organizations to distinguish between valuable investments in automation and inefficient expenditure​​.

Bringing Dark Data into the Light

Discovering and accessing dark data takes you on a data expedition within your organization. Here’s how you can illuminate these hidden data treasures:

  1. Data profiling: Data profiling tools sift through mountains of data to identify patterns, anomalies, and valuable insights. Running these tools on your datasets and data lakes is the first step to identifying underutilized data.
  2. Data integration: Once you’ve profiled your data, integrating various sources for a unified overview is key. Analyzing disparate data sources won’t give you a holistic view, and the insights derived are much less valuable.
  3. Data cleaning and preprocessing: Now that the issues of quantity and storage are taken care of, you have to make sure that as much of the data collected and collated is usable.
  4. Natural language processing (NLP): NLP acts as a translator, turning unstructured data like social media chatter and customer feedback into formats suitable for analysis.
  5. Consulting external experts: Sometimes, it takes an external expert to spot what’s hidden in plain sight. Consultants bring fresh eyes and specialized tools to unearth and utilize dark data.
  6. Auditing internal access and management (IAM) settings: It’s crucial to review who has access to what data. Sometimes, valuable data is locked away due to stringent access controls.
  7. Implementing in-house strategies: This involves training your team to recognize and value data that might previously have been overlooked.

Remember, the key is not just to find this data but to ensure it’s accessible and usable. Every byte of data in your possession could potentially hold value.

Extracting Insights from Dark Data

Once you’ve brought dark data into the light, the next step is to analyze it for actionable insights:

  1. Advanced AI algorithms: AI allows us to turn a jumble of disparate data points into a coherent, insightful picture.
  2. Machine learning and data mining techniques: These techniques evolve with your data, continuously improving their ability to extract meaningful patterns and predictions from it.
  3. Dark data analytics solutions: Comprehensive analytics platforms can process and analyze vast amounts of dark data, offering a bird’s-eye view of hidden opportunities and risks.

Transforming Data into Decisions

The real magic happens when analyzed dark data is put to practical use. Let’s take a gander at a couple of examples of how it can better various aspects of a business:

  • AI insights: Dark data can feed AI systems, enriching the insights they provide. For instance, historical customer data can enhance predictive models for future trends.
  • Operational efficiency: Analyzing previously unused log data might reveal inefficiencies in your systems, leading to improvements in operational workflows.
  • Risk management and compliance: Dark data can hold the key to better risk assessment and data compliance. By analyzing this data, businesses can pre-emptively address potential regulatory issues.
  • Enhancing customer experience: Dark data can uncover hidden patterns in customer behavior, leading to more personalized and effective customer service strategies, increasing satisfaction, and potentially reducing costs.

So, when dark data is effectively mined and analyzed, it becomes a powerful ally in decision-making, offering insights and opportunities that can significantly impact the bottom line.

Building a Data-Centric Culture

In today’s rapidly evolving data landscape, fostering a data-centric culture is not just a nice addition to a workplace, but a tangible necessity. Here’s how we can strive to cultivate such environments around us:

  • Emphasizing data literacy: Just like reading and writing, data literacy should be a fundamental skill within your organization (and, honestly, in general). It’s about ensuring everyone understands the power and potential of data.
  • Recruiting data skills: This involves seeking out individuals who not only understand data but can interpret and leverage it effectively. The goal is to secure additional value by adding members to your team who can navigate the data-driven world competently and with ease.
  • Providing training opportunities: Invest in your team’s growth by offering training in data analysis, machine learning, and other relevant fields. This could be through workshops, online courses, or collaboration with educational institutions.
  • Integrating data into decision-making: Encourage a shift in mindset where data is the starting point of every strategy discussion. This means integrating data analysis in regular business reviews and strategic planning sessions.

Company culture isn’t static and isn’t a “set it and forget it” deal – achieving any goal with regard to company culture, including data-centricity, will require constant, deliberate effort, but it will pay dividends in the future.

The Dark Side of Dark Data

While dark data holds immense potential, it also comes with its share of ethical considerations and risks. We’ve previously mentioned Seagate’s findings regarding dark data, and the figure of 68% on average. However, different research concluded that, depending on the industry in question, up to 90% of a business’s data can fall into this category.

 Consider the following:

  • Data privacy concerns: With great data comes great responsibility. It’s crucial to ensure that the pursuit of data insights doesn’t infringe on individual privacy rights.
  • Sustainability and environmental issues: Per the World Economic Forum, companies produce 1.3 billion gigabytes of dark data each day. The issue is so bad that data centers contribute more to global greenhouse gas emissions than the global aviation industry (equivalent to three million flights from New York to London) – and this problem is only going to get worse. 
  • Potential for misuse: There’s a thin line between use and misuse. For instance, consider the scenario where insurance companies could use purchased third-party data to influence decisions on secured property loans or mortgages, leading to a somewhat dystopian future​​.
  • Responsible data management: It’s not just about collecting and analyzing data; it’s also about managing it responsibly. This includes ensuring data security, adhering to ethical standards, and being transparent about data use.

Addressing these challenges head-on is vital in maintaining trust and integrity in the era of big data.

The Future of Dark Data

As we look toward the future, the role of dark data in the landscape of big data and AI is set to become more pivotal:

  • Continuous evolution: The realm of dark data is continuously evolving, driven by advancements in AI and machine learning. This evolution is reshaping how businesses view and use their untapped data.
  • Anticipating trends: Staying ahead in the game means not just understanding current data practices but also anticipating future trends. This could involve exploring new data sources or adopting emerging analytical techniques.
  • Leveraging dark data: Progressive organizations will need to become adept at leveraging dark data. This involves not just recognizing its existence but fully integrating it into strategic planning and operational processes.

The future of dark data is, surprisingly, bright. Businesses that can effectively navigate this evolving landscape will find themselves at the forefront of the data-driven revolution, armed with insights that can propel them to new heights of success and innovation, while contributing to a pressing sustainability issue at the same time.


Dark data might be the dark horse of data, but it offers untapped potential for strategic decision-making and innovation. When you recognize and harness its power, your organization can unlock new insights, enhance operational efficiency, and stay ahead in today’s data-driven world.