“Data democratization will catapult companies to new heights of performance — if done right”- Eric Matisoff, InfoWorld

“Every business is inundated with data from every angle. There is pressure to use insights we glean from the data to improve business performance. As a result of this incredible amount of data to process and new tech that helps non-technical people make sense of the data, there is desire and demand for data democratization.”

"Data democratization means that everybody has access to data and there are no gatekeepers that create a bottleneck at the gateway to the data. It requires that we accompany the access with an easy way for people to understand the data so that they can use it to expedite decision-making and uncover opportunities for an organization."

"The goal is to have anybody use data at any time to make decisions with no barriers to access or understanding.” says Bernard Marr, bestselling author of Big Data in Practice. You can read the original article by Bernard Marr quoted above here. It is an excellent article and Bernard is well respected in the industry so it is well worth your time.

So now that we have an understanding of what data democratization is, and what the benefits are for an organisation, let’s take a dive into the factors that contribute to achieving data democratization within an organisation and realizing the associated benefits.

Three Main Customer Problems Identified

We tried to get to the root cause of why companies fail to get data democratization right, and what works for those companies who do manage to get it right.

We looked at how companies are managing their enterprise data analytics functions today and using the architecture pyramid we discussed earlier as a reference point, we uncovered three key elements which need to work together to achieve effective data democratization within an organisation.

The Key Elements of Data Democratization

Now that we have uncovered the ‘secret sauce’ of effective data democratization, the next challenge is how do we implement it. There are only finite human resources available who have the talent to implement each of the key elements, so in order to deliver a scalable solution which can be replicated across many organisations we will need to rely heavily on automation.

Imagine if you were able to build a product with automated data democratization using industry-leading techniques and strategies, and then offered this product as a service for your business.

What would this be worth to you? We went out to the market to work out the scale of the problem facing customers today, how they are currently addressing it, and the value they would place on a solution which solves this problem for them.

Finding Potential Customers To Interview

We set out to validate our understanding of problems facing data analytics customers today.In our previous blog post, we invited our customers and users to share their views on the data analytics problems facing companies today, and their thoughts on what is needed in the next generation of data analytics products to address them.

The Response

We interviewed a range of customers to uncover some answers, we have collated our data below.

How Big Is the Problem Facing Customers?

We asked customers to rate on a scale of 1–10, how big the problem is to build, manage, and support each of the three enterprise data analytics tiers for their organisation.

What we found is most customers are relying on humans to solve the problem, who are supported by using tools including Excel and main cloud service providers (GCP, Azure, AWS).

There is no single tool on the market today which solves this problem completely. Therefore, customers are relying on a combination of people power as well as tools to manage their enterprise data analytics capability.

Customers are hiring specialist teams, either in-house or from a consulting agency, to solve these problems for them.

A common theme we found was that customers said there was a lack of data analytics maturity and skill within their organisation, and that training and change management were large contributing problems for them.

“In the industry I see a lot of problems around change management. Changing infrastructure or platforms is seen as risky. People aren’t taking advantage of the platform and tools to their fullest due to a lack of training and knowledge” – Data Analytics Customer Specialist, Cloud Platform Provider

Another common theme we found is that it is not the initial setup of the infrastructure, tools and data insights which is their biggest problem, but rather it is the ongoing maintenance, change management and ensuring consistency throughout their organisation.

Existing Tools vs. Cangler

We asked customers to rate on a scale of 1–10, how well their existing tools solve their problem and how well Cangler would solve their problem after describing our solution to them.

Across all customer problems, Cangler solved the problem better than the tools on the market today, but we believe we can do even better

What we found was that across all three customer problems, Cangler was viewed as solving the problem better than their current tools. This difference was particularly noticeable in the data acquisition & integration customer problem where Cangler was viewed as being almost 3 times better than the existing tools used today.

We found that the tools on the market today do not adequately solve the problems for customers on their own, so customers are solving this capability gap by hiring third-party data analytics consulting firms to provide the human resources and the expertise to build, operate, and manage their data analytics tools and projects.

According to consultancy.uk, $43 billion was spent on data analytics consulting services in 2017 and more than two thirds (67%) of the executives polled said they expect their organisation to increase analytics consulting spending in future.

Looking at the consulting cost per company, if we assume that a company will hire 5 data analytics consultants to help them that is a cost of $7500 per day ($1500 / day x 5 consultants).

Now if we extrapolate that cost over 261 working days in a year that adds up to a cost of $1,957,500 per year for an organisation in consulting fees alone.

Which companies are working on solutions to solve the problem of data democratization?

Data democratization is a relatively new field in data analytics. With that said, there are already some companies working on developing solutions to address data democratization in the enterprise such as Databricks, Teradata, Domo, Alteryx, and of course, Cangler.

Each company has their own unique approach to solving the problem. Only time will tell which approach companies will approve of and will adopt as their data democratization solution. One thing is for sure, the race to solve this problem is on.