Data democratisation: top tips for starting your own data-driven revolution

Data democratisation is a common boardroom priority across a number of industries – from financial services to retail to healthcare

It was one of Gartner’s top 10 strategic technology trends in 2020 and has continued to be a huge focus for organisations in 2021.

The democratisation of data has been described as the “ability for information in a digital format to be accessible to the average end user”. In other words, the goal of data democratisation is to allow non-data specialists to be able to gather and analyse data easily to aid them in their role. It’s the freedom, equality and true team culture that comes about by empowering every employee — not just data scientists and analysts — to make decisions informed by data.

The opportunity

Data, and the universal access to it, is key for today’s organisations to solve problems, create new opportunities and unlock the value embedded within their organisation – all of which can positively impact a company’s top and bottom line.

It pushes organisations to re-think and maybe even restructure, which often means driving a cultural change in order to realise financial gain. It also means freeing information from the silos created by internal departmental data, customer data and external data, and turning it into a borderless, integrated ecosystem of information.

The current state of play

Disappointingly, very few businesses are living and breathing the core principles of data democratisation currently. Our research last year initially suggested senior decision-makers were confident that they were opening up access to data sufficiently. However, when we scratched a little deeper, we found almost half (46%) of respondents believed that the democratisation of data wasn’t feasible for them.

IT infrastructure challenges were cited by almost four out of five respondents as a blocker to democratising data in their organisation. Performance limitations, infrastructure constraints and bottlenecks were also standing in the way.

This tells us that on a major scale around the world, many valuable insights from data aren’t being gathered quickly enough, projects are being stalled and the competitive edge is being lost.

So, what steps can organisations take to create an effective data democratisation programme of their own? Here are my top tips:

1. Assign a leader responsible for data

Organisations should consider recruiting a Chief Data Officer (CDO) to take ownership of its data. According to KPMG, organisations with a CDO are twice as likely to have a clear digital strategy in place. The role of the CDO is to drive the business forward on multiple departmental levels – from revenue growth and advancing internal innovation to improving operational efficiency.

Achieving true data democratisation relies on having the right skills in your people and triggering their imagination and innovative ideas. The CDO is one of the best-placed individuals to make knowledge of data an integral, normal part of the everyday life of an organisation.

2. Develop an overarching data strategy

Organisations also need a coherent data and analytics strategy in place to extract all of the insights they need. The most effective data strategies are integrated within the overall business strategy and establish common and repeatable methods, practices and processes to control and distribute data business-wide. Also, if the whole organisation is involved from the beginning, they will be more inclined to help drive a strategy forward.

A robust data strategy and culture that harnesses data democratisation also requires the right infrastructure to support it. When choosing a deployment model, organisations need to consider factors such as speed, cost, future requirements and the types of workload expected. Therefore, it’s important for businesses to make this decision after the data strategy is in place – to fully evaluate whether on-premises, cloud or a hybrid approach is the right option for what they want to achieve.

A hybrid cloud approach can often be the most efficient. It allows organisations to manage sensitive workloads on-premises, but also utilises the cloud – which is powerful when it comes to delivering large volumes of data to lots of people in real-time.

But no matter how brilliant an organisation’s strategy and infrastructure, it is worthless if its employees don’t buy into it.

3. Develop an employee education process

As organisations provide more teams and departments with access to data, they’ll need to build training into the process. Championing data literacy and trying to teach data as a second language within the business will be critical. Some firms go further and develop a Data Centre of Excellence (CoE) too.

Regardless of their level of technical expertise, everyone working with data can gain confidence by familiarising themselves with the components of the analytics stack in their organisation and the best practices that come with it.

AirBnB is a great example of a company doing this well. Despite having a data science team of more than 100 people, the company’s fundamental belief is that every employee should be empowered to make decisions informed by data. In an effort to scale its skillset, AirBnB has developed its own inhouse Data University and curriculum for its team.

4. Implement the right tech stack

Getting the tech stack right – or as right as possible – will help organisations ensure the resulting solution is fit-for-purpose. When scoping out options, they should keep in mind where they want to get to in the future and how they can enable more people to work with data to drive insights and support decision-making. During this process they should test the use cases of different departments and rather than giving demonstrations, let employees experiment with their own data and the tools to give them a clear idea of what’s in it for them.

The co-existence of multiple analytics tools within different teams and departments can add a layer of technical challenge but it’s one worth solving. Having teams with various tools at their disposal will provide greater opportunities for the right tools to be used at the right time for the right purpose and outcome.

Learning from the leaders

With all of this in mind, there are a couple of companies who are doing data democratisation well that demonstrate its value.

Firstly, digital banking alternative, Revolut. The UK fintech knows exactly how important data is to its success and reputation. It is an extremely data-driven company, maintaining around 800 dashboards and running around 100,000 SQL queries on a daily basis across the organisation. By embracing analytics and implementing an improved data management foundation, Revolut was able to unlock the true value of its data. Queries that used to take hours are now completed in seconds, enabling self-serve data analytics for all employees across all business functions. This is despite data volumes increasing 20x over the past twelve months.

The company wanted to ensure everyone has access to the data they need for their daily work in a simple and efficient manner. On top of this, the data science team uses the central database as a single point of truth, from which it can download real-time extracts and insights from at any time.

Revolut can now optimally analyse large datasets spanning several sources to assist in fraud detection, improving customer satisfaction and financial reporting.

Not-for-profit healthcare provider Piedmont is another great data democratisation example. It has successfully turned a massive 555 billion data points into an actionable source of information for its employees. By replacing its data warehouse and its core data repository with a high-performance in-memory analytics database, it has opened up access to data to more decision-makers who are now much more informed and able to improve the running of the company.

Hospital care quality, operation outcomes, and patient satisfaction have all improved as a result of Piedmont transforming into a data driven healthcare provider.

Data democracy in 2021 and beyond

Organisations are under enormous pressure to become data-driven, and as a result should be ramping up their efforts to democratise data access across the entire business. For many organisations earlier in the data journey, 2021 will be a year of continued investment in data literacy and organisational structures at a basic level. Businesses that are serious about maximising the value of their data will push to help employees of every seniority understand and utilise the data at their disposal to the best of their ability.


About the Author

Mathias Golombek, CTO of Exasol. Exasol is passionate about helping companies to run their businesses smarter and drive profit by analyzing data and information at unprecedented speeds. The company develops the world’s fastest in-memory database for analytics and data warehousing, and offers first-class know-how and expertise in data insight and analytics.

Featured image: ©Connect-World

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