How to achieve true data democratisation

By Helena Schwenk, VP, Chief Data and Analytics Office at Exasol

  • 1 year ago Posted in

Businesses today rely heavily on data to help them identify challenges, capitalise on opportunities and make timely decisions that could impact their bottom line. To harness the daily exponential increase in data, every employee within an organisation needs to be able to access and understand it. Otherwise, they’re unable use it effectively to deliver measurable business outcomes.

This means freeing information from the silos created by internal departmental data, customer data and external data, and turning it into a borderless, integrated ecosystem that’s used every day by all employees. Alongside data scientists and analysts, data democratisation allows the masses within a company to use data to inform their roles.

In fact, Gartner’s latest annual Chief Data Officer (CDO) Survey found that promoting data sharing and breaking down data silos is directly linked to high-performing data and analytics teams providing value to the organisation. It also predicts that by 2023, organisations that promote data sharing will outperform their peers on most business value metrics.

To achieve true data democratisation and the appreciation for data analytics at every level of an organisation, companies need a robust data culture and the right infrastructure to support it.

Creating a robust data culture

The most effective data strategies are integrated within the overall business strategy, with the whole organisation involved from the beginning. This enables organisations to establish common and repeatable methods, practices and processes to control and distribute data business-wide that are bought into from the start.

CDOs are the best-placed senior executive to head this up. A CDO can drive the business forward across the board, advancing innovation, operational efficiencies and revenue growth. Doing this relies on a breadth of knowledge and skills that span their organisation, from HR and marketing to sales and finance. This breadth means they can develop a strategy and infrastructure that is built upon every department having access to the data insights they need.

Training is crucial to achieving this. It’s impossible to be data-driven if your employees aren’t data literate. Employees need the tools and access to work with data so that they can understand it, analyse it, and apply their own ideas, skills and expertise to it.

Regardless of someone’s technical expertise, everyone can gain confidence working with data by familiarising themselves with the analytics available and the best practices that come with them through a centralised data strategy.

This isn’t all about number crunching either, data literacy is also about being a storyteller. Storytelling is a universal language that everyone can understand. Packaging up data insights as a story, recognising and interpreting the patterns and trends that data facts reveal and using the numbers as a means of grounding a story in truth, leads to convincing tales that anyone can tell.

When a greater number of people within an organisation can make decisions based on data – drawing conclusions and acting based on what’s happening from real-time data – the possibilities are exponential. Not only that, but employees can also free up time by using data to optimise their role, so they perform more meaningful and rewarding tasks and experience an increase in productivity and the ability to rethink operations and innovate.

Choosing the right tech stack

As well as a robust data culture, data democratisation requires the right infrastructure to underpin it. Unfortunately, our research discovered that four out of five data decision-makers find their current IT infrastructure makes data democratisation challenging.

Once again, a robust data strategy is crucial because this must be in place before organisations make infrastructure decisions. Choosing the right deployment model means considering multiple factors

such as speed, cost, and future requirements and types of workloads, such as prescriptive analytics, data science and/or the data warehouse.

Once all these factors have been assessed organisations can fully evaluate whether on-premises or cloud is the right option for what they want to achieve. Often, flexibility is important for organisations, which means a hybrid cloud approach can be the most efficient.

With a hybrid cloud model, organisations can manage sensitive workloads on-premises but also utilise the cloud, enabling employees to access datasets across a business’ premises or remotely. In fact, 96% of those we surveyed agree that a cloud model could make it easier to democratise their data. Firms can then not only turn their data into value faster than ever before, but also quickly adapt as the business evolves.

Start your data revolution

There is so much scope to extract value from data to drive a business forward - companies that unlock and master this discipline will be better equipped for long-term success. By not focusing on a cloud-only approach and choosing a high performance, flexible and scalable platform, organisations can derive business value from their data quickly, easily and cost effectively, no matter where they choose to store their data.

Developing a data strategy and culture that promotes a healthy appreciation for what data analytics can mean to every employee is a must-have for businesses in 2022 and beyond.

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