Data democratization

Data democratization | Why is it Important for Your Business in 2021

In a world lead by data, an enormous amount of data is getting generated every second. We know by now that a data warehouse adds a significant value to an enterprise, helping to improve decision-making processes, but what about access to the raw data? By implementing data democratization, you enable everybody in the organization to take advantage of data-informed decisions.

These days data democratization is often picturesquely compared to the availability of Bible reading to a common person in the age of literacy. Before it was available to the masses, the Bible was reachable only to clergy and people in high positions. Opening literacy to the general public has resulted in significant social changes. Similarly, data is often available only to data specialists and leaders of companies and organizations in today’s world. Data democratization should break such bottlenecks by bringing enlightenment in the form of data literacy to a broader circle of people.

The fact that data democratization is among Gartner’s top trends of 2020 speaks of its importance. We often mention data democratization alongside AI and ML trends and we often point it out as even more relevant in the context of new digital transformation.

In the following text, I will briefly bring up some of the challenges, benefits and risks behind the idea of data democracy and later in the second part of this blog, talk about adequate technology that supports data democratization foundation.

 

What is data democratization – hopes and fears

Data Democratization is the principle that implies that data is accessible to everyone in every moment and everywhere. In the case of an organization, it means that everyone across the entire organization has access to a holistic view of data – both technical and non – technical employees. In other words, data democratization erases the gap between these two groups.

However, one should not forget that data must be properly governed and privacy regulated, even more so, if access to it is being democratized. Precisely the importance of security in the context of data is why many might perceive data democratization as a negative rather than a positive term.

The main reason for a possible concern lies in a common fear of data breaches or data leakages (according to statista.com). However, in today’s chaos of rapid information fluctuations, data democratization is becoming mandatory for any organization’s success. According to business and tech trends, data democratization is inevitable. So, in order to embrace a positive social change, we should be better prepared to properly manage data and develop a positive data culture within the enterprise, with data democratization as a starting point.

 

2021 Business challenges

While Covid-19 caused an economic crisis and unemployment spikes in many parts of the world, the IT sector has been growing insanely. Many traditional industries have proven to be volatile and less critical than we have traditionally considered them.  For instance, oil prices have fallen rapidly during the pandemic. At the same time, the data has never been more important. As a result of the growing reliance on data and the exponential rate of digitalization, a significant number of people are trying to convert to the IT sector and data science and are figuring out how to learn technical skills to fit in as soon as possible.

Official numbers point out that, among others, the following jobs are in the Top 15 in-demand jobs in 2021: business development and sales professionals, specialized engineers, data scientists, and AI practitioners. All of them, as data-driven fields, should be and will be democratized. The key question that one should consider is: what is the proper way to democratize them?

Regardless of the Covid crisis, there have been several other data-related challenges that the IT sector has been facing for years now, to number a few:

  • Explosion in data volume – 6 zettabytes per year globally
  • Increase of new data consumers within an enterprise – data interactions went up by 5000% between 2010 and 2020,
  • New data types – growth of connected devices either social, mobile, or IoT
  • Data Cloud pursuit – >94% of centralized data will come from the Cloud
  • ML/AI growth – more than nine in ten leading businesses have ongoing investments in artificial intelligence
  • 67% of time spent just on searching relevant data and less on analyzing and getting insights

Another challenge for enterprises is knowledge standardization. For data-driven companies, misuse of data by non-specialists could lead to bad business decisions. On the other hand, knowledge standardization could lead to duplication of effort of different groups, both IT and business. Making data accessible to everyone doesn’t necessarily mean data will be transformed into actionable information. As a result, there is a potential risk of focus reverting to data and not to insights.

Data without context is irrelevant when it comes to decision-making. That is why maybe the most crucial business challenge of them all is finding the truth through data-driven analysis. In order to make informed decisions and cope with rapid changes in the marketplace, everyone in the organization should have an accurate view of the data that defines their business.

Having a single version of the truth within the organization is fundamental for decision-making processes.

 

Have you heard about data tyrants?

Imagine the person who collected a lot of knowledge within his 35 years of experience in data management in state government, for example. Introvert. Does not practice sharing his attainments. Perfectionist. His insights are trustworthy. All of his visualizations, analysis, reports, statistical models, datasets are stored in his computer and personal documents. The person is getting retired this year. His acquirements should be updated continuously when he’s gone. What’s the best way to manage it on time, to keep the project up and running, without any quality loss and delay?

Within the new data democratization culture, an aforementioned person is considered to be a data tyrant. The idea is to break tyrants by cultivating data democratization. Democratization won’t let anyone have the ability to become a tyrant.

*Idea of data tyrants is borrowed from the Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering, which I highly recommend as it is a manifesto of data democracy, which speaks about data democracy in the context of data republic with data citizens who manage it properly, fighting against data tyrants.

 

Benefits and risks of Data Democratization

Data democratization wrecks the walls between IT and the business sector, breaking annoying silos. Doing so, it establishes greater collaboration across the enterprise and even beyond. Data sharing is essential to drive business value through data.

Centralized, governed data available to relevant people is one of the business’s catalysts. Democratization helps unify relevant data and establish a holistic and accurate view of data for any side of an organization. Popularizing, disseminating, and crowdsourcing data along with its intelligent technology support enables faster progress and reduces the cost of operations. In addition, relevant data is easier to find.

Data democratization builds greater trust and compliance by providing consistent and easy-to-use access to data. The process of data democratization opens a positive data culture. It minimizes the risk of creating data tyrants. Besides that, democratizing data science breaks skills and talent bottlenecks that are currently holding many organizations back, not allowing them to fulfill their full data potential.

Security is the top risk of democratization enablement. However, if properly managed, data democratization is an actual solution for security management as well.

Fear of data breaches is justified. Even technology giants (Facebook, Google, Amazon) failed miserably once they faced a data security crisis. And still, they are not doing much about it. For them, regarding their profit, paying fines appears to be more cost-effective than coping with the problem and adequately managing data protection. However, the encouraging fact is that nowadays, global consumers are more loyal to brands with solid data practices. Because of that, consumers are more and more likely to boycott a company that does not take data protection seriously.

Furthermore, low-code development brings data science to the masses. But what it takes for this kind of projects to work is expertise, and not the one you can gain while watching a YouTube video. It’s necessary to put a significant effort into a proper governance regime.

New technology often runs into a lack of trust from business and tech users. So, there is a great chance that there will be distrust when establishing data democratization, which is why it is not only important for the whole process to flow gradually but also to educate and communicate with everyone involved and to keep the whole process transparent as possible.

[READ MORE: Part two of this blog that touches upon Data Governance as a first step to data democratization relations, and also speaks about technology that supports it!]

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