Dark Data - Meaning, Present Trends, Pros, Cons and Risks

When we talk about organization data, all you think about is big data and other existing forms of data. Have you ever heard of Dark Data? Might be no or might be yes. Dark Data is unknown, untapped and unused data of an organization. You will find it strange, but many organizations are not even aware of Dark Data.

 

Now, you might be wondering how it is possible for unknown data to exist in the AI world?  In this blog, we will read everything related to Dark Data, from its definition to uses. We will also look at its pros and cons.

 

(Take a look at What is Data Integration)

 

 

What is Dark Data?

 

While reading the word, Dark Data, you might be relating it with some similar words like the dark world or the underground world. Though, not exactly the same meaning, Dark Data is similar to the underground world in one way, that not everyone is aware of its existence. 

 

In the case of dark matter physics, the similarity is that both contain universal information. Keeping the comparison apart, in technical language, Dark Data is data that is created during different computer network operations. Though, Dark Data exists but it is not used for any sort of operation such as insights creation and decision making.

 

Dark Data is a part of big data. As big data grows for an organization, the amount of Dark Data inside it also increases. The Gartner dictionary defines the term Dark Data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes.

 

Other purposes here refer to analytics process, business relationships, insights derivation, and decision making. The organizations and institutions don’t use Dark Data and often retain it for compliance purposes only. The storing and securing of data typically incur more expensive than the actual value. 

 

In fact, many organizations aren’t even aware of the fact that their data is being collected. This Dark Data is generated and gathered by sensors, telematics and analog-to-digital conversions.

 

Why do organizations retain their Dark Data?

 

Organizations and institutions retain Dark Data for multiple reasons, which include following purposes:

 

1. To help companies to track their activities.

2. For record keeping.

3. For regulatory compliance.

4. For better analysis.

5. For future business intelligence technology.

6. To avail potential return profits.

 

What is Dark Data analytics?

 

Dark Data analytics is a software that helps the organizations to better locate, tap and identify their Dark Data. The Dark Data analyzed here can be used for critical business making.  The organized Dark Data analytics and overcome the limitations and risks caused by unorganized Dark Data. 

 

It enables the less technical employees to understand the needs and requirements of their organization. A Dark Data analytics solution helps in providing a comprehensive, insightful and accurate understanding of users’ data to the organizations. In simple words, it helps in creating a big picture of their environment. 

 

(Related blog - Data Analytics and its Types)

 

 

What are the present trends in Dark Data?

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Present trends in Dark Data

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The basic trend in Dark Data is to effectively manage everything of an organization's data. There is no doubt that data is fuel for an organization, but still, most of the organizations are unprepared to address associated challenges with it. The significant Dark Data trends include:

 

Future for business success

 

The Dark Data collected today will become more valuable over the next 10 years. It will act as an influence to their decision-making process.

 

Data skills for future jobs

 

Most organizations believe that data skills are an important measure for selecting workers in all roles for their organizations. This not only applies to an IT firm, but all kinds of companies and firms nowadays are looking for data literate employees.

 

Lack of tools required for data stability

 

Though people and organizations are aware of the importance of data, their acknowledgement of necessary resources, tools and skills required for making data organized and usable is limited.

 

Dark Data skills gap

 

Many organizations face data skill gaps, as their employees aren’t willing to learn new skills. Thus, the chances of improvement are also limited.

 

 

Real world uses of Dark Data

 

Currently, in AI world, Dark Data is in use to deliver following functions:

 

1. To fuel AI powered solutions.

2. To increase data wealth stored.

3. To produce deeper and more accurate insights.

4. To create more productive and innovative business strategies.

5. Helps the organization in building management and leadership processes. 

6. To improve quality assurance.

7. To detect and correct the process errors.

8. To search privacy loopholes.

9. To secure vulnerabilities.

10. For potential compliance violations.

11. To create new data management skills.

12. For growing rapid technologies, such as IoT.

13. For long- and short-term analysis.

14. To access quantifiable results.

15. To improve the healthcare facilities.

 

(Get to know the relationship between Big data and Cloud computing)

 

Pros, Cons and Risks of Dark Data
 

Pros of Dark Data

 

Dark Data has following advantages in AI world:

 

1. Dark Data can be used to frame a complete view of product usage, consumer habits, and overall performance.

2. The Dark Data can be used to carry incredible insights for design, engineering and product development.

3. The Dark Data if utilized properly can change the entire potential of the company and directly affects its bottom lines.

4. Dark Data, in the era of social media, plays a vital role as it connects the customers with the consumer base. And, customers are important in the current world, as they not only consume your products, but also help in promoting your business and act as an ambassador for your service.

5. Dark Data can potentially assist the organization by driving new revenue sources.

6. It helps in eliminating waste and reducing logistics costs.

7. The Dark Data helps the organizations in identifying dark bits and in mapping them to possible business uses.

8. Dark Data helps the organization with regulatory compliance purposes.

9. By properly analyzing the Dark Data, companies can unfold the trends related to their customers, competitors, and marketplace.

10. Dark Data can help the companies to mark new levels of innovation and resilience.

11. Dark Data help in achieving three major goals of modern business i.e., customization, convenience, and mobility.

 

(Recommended blog - Compliance Testing)

 

Cons of Dark Data

 

Everything loaded with some benefits is embedded with some demerits. The cons of Dark Data are as follows:

 

1. Management of Dark Data is an expensive as well as complicated process.

2. Analyzing Dark Data requires a good deal of time, resources, and available tools to get organized and structured.

3. Dark Data contains information related to the company and if gone to the wrong hands can cause serious damage to the industry.

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Risks of Dark Data

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Risks involved in dark data

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The risks of Dark Data are quite fewer as compared to its merits. And that too arises when the data isn’t controlled and managed well. The major risks involved in Dark Data are:

 

1. Intelligence risks

 

If the Dark Data contains sensitive information like a competitive advantage, partnership information, business relationships etc., it can severely affect your organization if used by hackers.

 

2. Financial risks

 

If Dark Data contains legal information such as credit card information, it can cost the users financial or legal liability.

 

3. Reputation risks

 

Being hacked and used by hackers not only harms the potential and financial capability of the company, but also affects the reputation of the company as its digital security protector.

 

(Learn how to manage risk through Risk Assessment and Management)

 

There is no doubt that Dark Data has several bright aspects hidden in it. And in the coming time, it can crave the important needs of an organization. But the enterprises and organizations need to find right Dark Data solutions and ways to overcome data challenges to lead this hidden data in an effective, organized and progressive way.