All CategoriesData Analytics with R, Excel & Tableau

How to Include Dark Data in Analytics Strategy

Dark data is any information that an organization gathers, processes and stores through organizational activities, but doesn’t use in any meaningful way. Generally, dark data tends to voluminous data that lacks any structure. Organizations gather it for compliance or legal purposes and so are hesitant to remove it off their systems. Sometimes, they collect it with a purpose in mind but forget about it when the goal they set out to achieve seems illusive. In this article, we’ll explore how this data, which is a great source of insight and help in decision-making, can figure in any analytics strategy.

Importance of Dark Data

Dark data is hugely important. Overlooking the wealth of information that we have is a big mistake. Especially, when tackling problems on which data exists. For example, consider this scenario.

The ocean is changing both – chemically and biologically. We have oceanic data from the 1970’s and 80’s that can help us understand this change. But the problem? It’s not easily accessible.

What’s the alternative? To begin gathering data now and interpret later? It’s an option and we should start on it. Having said that we also need to bring to life dark data that is lying dormant to help us be ahead of the change. And, that’s what they did. Environmental data on Zooplanktons and other factors that affect oceanic change are freely available at the BCO-DMO to any researcher, who can contribute to understanding the changes in the ocean and thereby climate.

The Challenge

Organizations tend to ignore dark data because it may be a challenge to restore it. They could be in a variety of formats that would, in the past, require lots of hands, effort and money to make useful. But now things are different. With better computer vision, cognitive analytics, pattern recognition, and other advance technologies, processing voluminous data without structures has become easier. Companies that invest in industry research like Deloitte are proclaiming the beginning of the era of ‘dark analytics’ – analytics that will bring businesses and organizations meaningful insights from dark data that available structured data assets fail to provide. How can CIOs and CDOs leverage the benefits of dark data?

Inspect First

Most companies have data in some form or another from the past. This data is most likely in some physical form that makes it hard to analyse and interpret considering their volumes. Therefore, most companies choose to overlook this data during their digital transformation thinking that they will get to it later. But, will they? The key to leveraging dark analytics is identifying all available data repositories and devising a systematic plan to digitize it for easier analysis and future use.

Identify Important Data Sets

Of course, all data could potentially be useful. And it may be tempting to get to all of them simultaneously. But in the interest of time and effort, it may be wise to prioritize. Digitize and interpret those data sets that promise to offer the highest value to the business or organization.

Be Responsible with Dark Data from Past

With the power of dark data comes great responsibility. As physical forms of unstructured data are digitized, it is important to consider the ethical implications of such a transformation. Most importantly, it is important to protect the integrity of data by maintaining quality, as well as, security to avoid compromising sensitive information.

Plan for New Dark Data

Dark data does not only comprise of existing data under the radar. It also potentially is any data will enter the systems without a definite purpose or plan for utilization. The IoT will produce, according to a report from Cisco, around 500 zettabytes of data every year from 2019. That is a lot of data to analyse even with the advancements in technologies. Industry leaders will have to effectively strategize to ensure that the dark data of the future is the least relevant data of all that they gather.

Check with External Data

Let not dark data lead you to the dark. Do not blindly trust data from the past because it seems promising now. Make sure to find any data from outside sources that may be crucial for your decision-making process in the present. Apart from helping you evade risks external data will also provide you with a new point of reference. Like the before and after scenarios, new external data can help you identify the differences between the past and the present.

Focus on Results

Data is only worth what you can achieve with it. This does not change for dark data. The level of difficulty in utilizing dark data depends on the technologies available to the organization, the level of expertise in their rosters and the amount of dark data that they possess. Any leader looking to achieve success with this unruly and possibly difficult data must set their eyes firm on their objectives and focus on the results that they will achieve by investing in dark analytics.

The idea may not be suitable for all stores of data available. And, it most likely will be better for some than others. Leaders must establish a compelling business case before venturing into the mysterious and obscure area of dark data and dark analytics.

Suggested Reading

 

Data Analytics at Zee Entertainment

All You Need to Know About Data Analytics

 

Tags

Rohan Kumar

First-gen Rohantosh. Admirer and critic of all things tech. https://medium.com/@acadgildwriter

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Related Articles

Close
Close