Dark data is considered as a subset of big data, but it accounts for most of the overall amount of big data obtained by organizations in a given year.
Companies do not typically analyze or process dark data for various purposes, but this does not diminish its relevance in terms of business value.
There are two ways to look at the significance of dark data.
According to one perspective, unanalyzed data includes undiscovered, essential insights and represents a missed opportunity.
The other point of view is that unanalyzed data can cause a slew of issues, including security and legal matters, if not treated properly.
What is Dark Data?
Organizations collect massive amounts of data in the hope of improving their products and services.
For instance, a business can collect information about how users interact with its products and internal statistics about software development methods and website visits.
However, a sizable portion of the data obtained is never analyzed.
IDC estimates that 90% of unstructured data is never explored. This type of data is referred to as dark data.
While the definition of dark data varies by company, the following categories of unstructured data frequently considered dark data:
- Customer Data
- Previous Employee Data
- Log Data
- Financial Reports
- Raw Survey Data
- Account Data
- Email Messages
- Notes or Presentations
- Old Versions of Important Documents
Why is dark data managed the way it is?
This is surprising because businesses collect data with the expectation that it would be helpful.
Firms make significant financial investments in data processing, so data should be valuable on financial and non-financial levels.
The following are only some of the explanations for the accumulation of dark data.
Consider a bank that conducts online credit card application analysis. The credit card marketing team is primarily concerned with customer data and qualifications, with little regard for how the customer arrived at the application page.
The unattended data may have revealed critical information about the bank’s website and application page’s usability. However, this factor does not receive any priority.
Departments within large organizations also have their data collection and storage procedures unknown to other departments. As a result, data remains unused, even though it applies to other agencies. This is a problem of process.
When different technologies and tools carry out data collection within the same organization, these technologies and tools will not communicate due to technical constraints. This excludes the collection of all data and the creation of a unified image.
This is particularly true for businesses with disparate information technology systems and formats. For instance, it can be challenging to incorporate audio file contents from the call centre with website click data. These issues affect businesses that are just getting started with data analytics.
Companies can encounter the following points when dealing with dark data:
Indeed, businesses that have acquired a large amount of dark data are now faced with issues.
If dark data is not correctly managed, it may result in legal, financial, and other complications.
Legal Issues: If the data stored is regulated by law, such as credit card data, its exposure may expose businesses to financial and legal liabilities.
Loss of reputation: Businesses is regarded as data custodians. Thus, any data loss, particularly sensitive or confidential data, can result in a loss of reputation.
Intelligence risk: Businesses can lose proprietary or confidential data about their activities, products, financial status, and business plans due to intentional or accidental disclosures. This could harm the business.
Opportunity costs: Suppose a business chooses not to engage in the analysis and processing of dark data, but its competitors do. The competitors are more likely to edge ahead of the competition due to their dark data insights. That is the expense incurred by the business as a result of missed opportunities.
Cloud Integration- Illuminates the Dark Data
Cloud Integration enables more efficient data collection and storage.
Organizations with many endpoints frequently experience delays in the group, transmission, and data integration from those endpoints. Many gather merely summary data from those endpoints due to work required.
As a result, detailed data is frequently unavailable, accessible only at a single endpoint, and incompatible with other endpoints.
Cloud technology, which is becoming increasingly resilient, enables data to be collected directly from endpoints; data may also save in the cloud as it creates, guaranteeing that all data is collected.
The cloud connection enables the integration and storage of data quickly and economically.
Cloud storage allows businesses to access all of their data without requiring time-consuming and costly data transmission and re-transmission within the organization.
Importance of Cloud Integration
By revolutionizing dark data and integrating it under one roof, all departments can develop a culture without consulting IT.
Business executives should facilitate this behaviour shift by assisting department heads in innovating how their teams are deployed and operated, leveraging accurate data to make innovative and impactful decisions.
While data democratization is critical, robust data governance must ensure that data is used efficiently and accurately across the company.
However, cloud-based data integration does not imply a loss of control since each user of the central platform can grant a role or attribute, indicating that they have specific access levels from the moment they log in.
Integrated cloud solutions enable IT leaders to certify data sets, indicating which the firm or a specific department has accepted data, or they can create specific levels of infinite customizable data permissions. Administrators can design entitlement policies that control who has access to which data in a dataset.
Whether it’s sheltering the IT team from ongoing data requests or utilizing Artificial Intelligence to activate chatbots to communicate with your customers, the possibilities for uncovering and using dark data are limitless.
Once a data-driven culture has been established throughout your organization, you are only limited by your innovative application of data.
In today’s highly competitive data-driven business environment, it has become critical for businesses across all industries to acquire, store, and analyze the complete spectrum of available data.
Dark and traditional data sources—to make more informed business decisions and achieve better business outcomes.
When semi-structured, image, audio, and in-motion data is ignored, analytic insight is lost, essential decision harming, and commercial value is lost. Private, public, and hybrid cloud infrastructure, streaming analytics, artificial intelligence/cognitive technologies, and robust new analytic methodologies illuminate dark data like never before, revealing deeper, actionable insights.