Democratising data

Naggi Asmar at Matillion explains how to democratise data across your business for analytics success

 

Businesses worldwide still aspire to have a data-driven culture but 2023 poses a challenge to the modern data team. They will be expected to produce even more with massive amounts of data while battling shrinking resources and diversely skilled team members.

 

Their incessant demand for data roles means the volume of related vacancies is growing at a rapid rate, and an already stretched labour market is struggling to keep up with the supply that’s needed. The latest IT Skills Report from DevSkiller, for example, reported a 295% global spike in the number of data science-related competencies sought by employers during recruitment processes during 2021. Clearly, organisations are committed to investing a great deal of money and time into bolstering their data teams, but the talent pipeline simply isn’t flowing quickly enough.

 

Retention struggles are exacerbating this issue even further, with our research showing 87% of global data decision-makers believe their organisation struggles to retain talent. When you add the fact that more than two-thirds of data users are considering leaving their job in the next two years, it’s a concern that has never been more pressing. We’re already hearing that in some sectors, recruitment demand outstrips supply by such a rate that data professionals are regularly being tempted with better offers from elsewhere, creating more talent churn within businesses and disrupting their efforts to make data more consistently useful.

 

Don’t ignore the data skills gap

Bucking that trend means recognising that the data skills gap is a reality to navigate, rather than a problem to solve. In a period of such turnover of talent, you need to prioritise solid frameworks that allow you to be productive with data, even when you inevitably lose people and have to train new ones.

 

Part of that comes from prioritising data productivity at every opportunity; in other words getting your data analytics-ready quicker. Right now that’s a common challenge, with many organisations bogged down with migration and maintenance tasks. Two-thirds of those we surveyed (66%) believe their business is wasting time on data preparation, while 81% see poor or incomplete data migration cost them opportunities and revenue, to the tune of up to $43.5 million annually. This is time and resource that could be spent on more strategic work that produces real insights and informs decision making.

 

This is where having a data philosophy comes in; a robust, process-focused approach to data within your organisation that can help you stay competitive and make reasoned decisions amidst constant internal and external change.

 

We’re all aware of the current economic and labour climate, but business leaders, in particular, are being asked to do ‘more with less’. In the context of data, that means ensuring the talent you do have at your disposal is equipped to be as productive as possible.

 

Power to the people: democratise your data

Every data philosophy should help to make data more accessible to all corners of the business. It’s about encouraging a data-driven culture, with the end goal of ensuring as many people as possible have access to tools and knowledge that can give them the right insights at the right time. Being a genuinely data-driven organisation means that data isn’t merely the preserve of siloed teams of professionals, but a resource that any employee in any department can tap into to improve efficiency and solve problems.

 

On top of that, visualisation and integration tools are now becoming more intuitive and beginner-friendly, making it simpler for less data-savvy employees to work with complex assets. Low-code and no-code tools are also proving immensely valuable, and they are making it easier for those with less advanced programming skills to drill into data and analyse it according to their own requirements.

 

Business users need be able to tap into key business insights quickly and with minimal effort, and by and large, that process is becoming far easier to achieve. Data is becoming more accessible and usable for wider teams, and freeing up data teams to reallocate time to taking advantage of what the cloud has to offer. 

 

Get your technology cloud-ready

Work still remains, however. Successful data strategies also rely on data being analytics-ready – transformed from iron ore into steel, so to speak. Historically, data teams have relied on outdated Extract, Transform and Load (ETL) or point solution ELT technology to do that. But many of these platforms are unsuitable for working in the cloud, and cannot sufficiently scale with the influx of data being generated.

 

This is because the modern data estate is spread over an array of applications in a variety of different formats that often don’t communicate well with each other. Putting steps in place to ingest and integrate data from any source into any cloud, regardless of underlying infrastructure, is the way to get a competitive advantage and ensure people across the business are in the best possible position to extract game-changing insights in real time.

 

Let your data philosophy guide the way

The war for talent in the data world is a problem that clearly isn’t going away, at least in the short term. As such, a guiding data philosophy is a must-have; it can be an oasis in the desert, helping maintain continuity amid a turbulent job market, supply chain disruption and the many other uncertainties affecting businesses currently.

 

Of course, it’s not an instant fix for all your problems, but rather a strategy that must be formulated with various departments, and with the specific needs and objectives of the business in mind. Becoming truly data-driven is a long-term journey, but you can lay the foundations now to put your business on your way to data productivity.

 

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Naggi Asmar is Chief Engineering Officer at Matillion

 

Main image courtesy of iStockPhoto.com