Data is crucial for any business, but many businesses report that nearly half or more of their data is unutilized or “dark.” Dark data is data that businesses collect and store but don’t utilize for other purposes like analytics or monetizing. It seems paradoxical that organizations collect vast amounts of data, yet most of it remains unused. However, dark data can be used to uncover valuable insights, inform decision-making, and improve a business’s competitive edge.
What Is Dark Data?
Businesses collect seemingly endless amounts of data, but not all of it is used for other purposes. Dark data or unutilized data is a term coined by Gartner that refers to data that is collected, processed, and stored but never analyzed or used. This type of data accumulates because businesses store all the data they collect in large data repositories or lakes, but some of it isn’t easily usable because it’s not as easy to track or retrieve.
Some types of dark data include:
- Customer support logs
- Internal communications
- Email archives
- Surveillance video footage
- Duplicated data
- Network or application logs
- Social media posts and interactions
- Raw survey data
- Previous employee data
- Internet of Things (IoT) sensor data
How Does Unutilized Data Differ From Structured and Actively Used Data
Dark data can result from different types of data, including structured, unstructured, or semi-structured data. Structured data is any information that is added to a clearly defined database or spreadsheet before it is stored. Dark data that results from structured data includes things like server log files, Internet of Things (IoT) sensor data, customer relationship management (CRM) databases, and enterprise resources planning (ERP) systems.
Although dark data can form from structured data, it is different from both structured and actively used data. This is because structured and actively used data is organized and formatted so it can easily be accessed and analyzed. Meanwhile, dark data is collected and stored but not analyzed or actively used.
Why Does Unutilized Data Accumulate?
Unutilized data can accumulate for several reasons, although it may seem counterintuitive to a business’s operations. These reasons include:
- Lack of data strategy: Businesses may not have a sound data strategy or high data literacy that helps them understand the value or relevance of dark data.
- Complexity of unstructured data: Unstructured data can be in complex formats and make data analysis difficult, leaving it discounted or ignored.
- Outdated legacy systems: As businesses upgrade their software or hardware systems, older legacy systems can be retired, leading to data stored in them going dark.
- Compliance and regulatory concerns: Many businesses must comply with governing standards that require them to store sensitive data for certain lengths of time. They may continue storing it after the mandatory period is up, resulting in it going dark or becoming hidden data.
Having incomplete or ineffective data integration processes can also lead to data going dark, as certain datasets may become inaccessible or not correctly linked to other data sources.
Unlocking the Potential of Unutilized Data
Dark data can create challenges for businesses if they don’t realize its potential. The sheer volume of unutilized data can lead to major storage costs, cybersecurity liabilities like data breaches, missed opportunities for insights, and more. If businesses recognize and utilize the power of dark data, they can experience improved customer interactions, an enhanced competitive advantage, better data quality, and more benefits. Fortunately, businesses can unlock the untapped potential of unutilized data through a few methods. They include:
Relying on Artificial Intelligence
Artificial intelligence (AI) can be used to extract meaningful insights from unutilized data. AI, specifically machine learning (ML), can help analyze large amounts of unstructured and dark data, helping to detect patterns, connections, and potentially valuable insights that would be hidden otherwise. ML automation can also help businesses comply with data privacy regulations by redacting sensitive information from stored data. By using AI to extract insights from dark data, businesses can identify issues and optimize different aspects of their operations.
At CloudFactory, businesses can take advantage of our AI data and generative AI services that help uncover insights from dark data.
Prioritizing Data for Analysis
Many businesses forget about the data that they don’t utilize, so it never gets organized or prioritized for analysis. By making it a goal to organize and analyze this dark data, businesses can get insights and information that they may be overlooking. To organize dark data, organizations should:
- Break down data silos that can hinder collaboration, which involves making the data in the silos available to other teams that may find value in it.
- Improve data management by understanding what data exists within the organization, starting by classifying all the data to get a complete view.
- Establish clear policies for data storage, data security, access, and usage going forward.
Leveraging Cloud-Based Platforms
Organizations can also lean on cloud-based platforms to help them process dark data efficiently. These platforms can help discover, manage, and leverage dark data so businesses can classify and integrate it. This allows for better data governance, risk management, and regulatory compliance.
Developing A Strategy From Unutilized Data
Businesses that want to leverage the untapped potential of dark data to drive smarter and more informed decisions, enhance operational efficiency, and unlock hidden opportunities will need to develop a related data strategy. To create a dark data strategy, organizations should:
- Assess their current data collection and storage practices
- Identify high-value dark data sources, such as log files, financial statements, geolocation data, raw survey data, etc.
- Invest in data analytics tools and AI-driven solutions
- Establish clear data governance policies
- Continuously monitor data usage strategies
Businesses can also turn to data experts at CloudFactory, which is a global leader in providing workforce solutions for machine learning and business process optimization. CloudFactory’s managed workforce strategy and experienced data analysts can help your business establish a sound strategy for unutilized and big data.
Create a Dark Data Strategy With CloudFactory
Unutilized or dark data is collected and stored by organizations, but not utilized. However, this dark data can be an untapped resource that provides actionable insights and allows for data-driven decision-making. Creating a data strategy for your business’s unutilized data is crucial to tap into this worthy resource. For more information on creating a dark data strategy, contact us and consult with CloudFactory experts today.
