The future of data democratization is here. Investors are about to take advantage


By Kate DuBois, Managing Director Skaï, Market knowledge

There was more data created in 2020 than any other year so far and the world is on track for exponential data growth over the next five years. Hidden within those zettabytes are predictions of trends and consumer needs that will emerge and represent major opportunities for good brands. But if organizations aren’t able to digest data and turn it into actionable information, they will make decisions that will keep them behind. As investors assess which companies to pursue, they would be wise to carefully consider how data-driven their goals are. The most advanced organizations with the greatest potential for success are those that have democratized data across the enterprise to ensure that everyone at all levels is making decisions based on the same data.

The true democratization of data analysis is still in its infancy. But the way forward is clear and similar to the path we have already taken for widespread internet use, with similar opportunities for investors.

How the Internet has democratized, decade by decade

Internet as we know it today has begun as local and global computer networks in the 1960s, used primarily by computer specialists and national agencies. The following decade saw the expansion of the interconnectivity of computer networks through the development of new backhaul protocols, although the user base remained largely the same. Throughout the 1980s, the PhoneNet system – a network built using dial-up telephone lines – allowed even more people to access the Internet and send the first international emails, even if you had to. still need expensive computer equipment and reliable connections to access everything. True democratization began in the late 1980s and early 1990s: The invention of Sir Tim Berners-Lee HTML, HTTP, URLs, and the World Wide Web have allowed the Web to evolve rapidly. The first web browser, also invented by Berners-Lee, opened the Internet to ordinary people without special computer skills. By 1995, mainstream websites like Amazon, Yahoo, and eBay were online and the The World Bank reported that about 9.24% of Americans identified as Internet users. This year, 93% of American adults are online.

The essential forces of democratization: technology & demand

The democratization of the Internet has been achieved thanks to two forces acting in tandem: technological innovation and user demand. Today we are at a crossroads in data analytics where these two forces are intensifying. There is more data than ever before, and it is growing rapidly. In response, the field of data analytics has advanced to help businesses understand large amounts of unstructured data. Advanced data analytics solutions can collect external data sources relevant to a business, extract meaningful context from them to explain both What so happens Why, then make that information available and understandable so that leaders can take informed action. Increasingly, these leaders recognize that their entire business would improve if everyone had access to the same single view of information. Here are some of the benefits of democratizing data:

  • Faster and better decision making. This can translate into a market-leading advantage as companies take advantage of emerging trends and consumer demands.
  • More consistent decisions. A unified, widely accessible view of data means the entire organization makes aligned decisions.
  • Empowering employees. With access to data, teams and individuals can feel more confident in taking ownership of a business problem.
  • Improved operational efficiency. Data Scientists spend almost half of their time make the data usable. Streamlining internal processes and reorienting data teams to more strategic work can save a lot of time and energy.
  • More ROI from investing in data. Empowering everyone in the organization to make data-driven decisions will ensure you get the most out of every data point you buy.
  • Better understanding of the customer. There is a wealth of external data about your market, your customers, and your potential customers. Understanding this data leads to decision making focused on meeting consumer needs, resulting in better customer experience and greater market share.
  • Faster adaptation to new circumstances. When the market or customer changes, you will see it in the data. You can then make proactive rather than reactive decisions.

Given these advantages, it is no wonder that a recent Google Cloud Survey and Harvard Business Review industry leaders have shown that 97% of respondents believe that access to organization-wide data and analytics is critical to their business success. However, only 60% believe their organizations are effectively distributing this access today. a Exasol survey out of 500 executives and data professionals, 90% of respondents prioritize the democratization of data for their business.

The demand is there. But do we have the technological tools to make data accessible to everyone?

The challenges of data democratization

There are good people, process, and technology reasons why many organizations have yet to fully democratize access to their data, including:

  • Organizational silos. In some companies, teams are set up to work independently. They don’t share the internal and / or external data they collect to make decisions, and there isn’t a strong culture of sharing ideas cross-functionally.
  • The use of specialists. Many organizations have long relied on data scientists, analysts, and other experts to interpret data. Some of these teams became so inundated with requests that decision makers either developed workarounds or stopped looking for data altogether as part of their process. Changing these entrenched cultural paths can require a complete overhaul of the business process, a tall order.
  • Data complexity. New technologies are creating ever larger data sets. Unless this data is collected and contextualized, the average person has a hard time understanding it.

Dashboards and data visualizations have emerged as possible solutions to these challenges. The Exasol study previously mentioned showed that 82% of respondents use dashboards to communicate information within their organization. And it’s easy to see why. Dashboards can be introduced into each team’s process, eliminating information silos. Their simplicity means you don’t have to be a data expert to understand them. But that simplicity also means that the data being shared is quite shallow, without enough background or context to answer complex business questions. This is just one of the reasons many respondents to the Exasol study indicated that their organizations routinely ignore the dashboards they have put in place. The other reasons? Too much time to interpret, too much information overall and not sufficiently tailored to individual needs. It can all be summed up in one review: Data dashboards don’t tell stories, and stories are what are essential for communicating data and analytics results.

People are curious and think in terms of questions; this is what made the invention of the web browser and the Google search bar so revolutionary in the democratization of the Internet. Internet users could search for the web pages and information they were interested in, rather than coming to the web with in-depth knowledge of its content. Data analysis needs a similar research-driven tool to fuel true democratization.

Three steps for a real democratization of data

The easy-to-use data democratization tool of the future will combine the power of big data and AI with the ease of use of Google to deliver data stories and insights in response to direct questions from individual users. Organizations can begin the transition to true data democratization by following three steps to overcome today’s technological barriers:

Step 1: Build a strong database that includes a wide range of internal and external data sources that cover the entire relevant market, not just a single brand or product. Continuously updated data feeds will ensure that all information is always relevant and reveals changes in the market landscape in time for leaders to make responsive decisions.

2nd step: Use advanced analytics to make data insights understandable. Today, powerful machine learning (ML) and natural language processing (NLP) algorithms can extract context from data by creating simplified representations of text and applying macros (or rules) to those representations to determine semantics. From there, NLP can identify the sentiment behind a data point and associate it with taxonomy values ​​- or details – that are unique to a specific market. This makes it possible to explore, for example, consumer opinions on a particular skin care ingredient or recent patent filings for product packaging.

Step 3: Develop information in a user-friendly experience. The future of democratized data will follow Google’s path, with tools that give individuals in an organization access to easy-to-understand, data-driven stories that answer questions and solve problems. The key is that these tools are responsive to individual user needs; it’s what’s missing in today’s data visualizations and dashboards, and it’s what made internet search a real game-changer.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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