Senior Data Engineer, CTS
I recently had the pleasure of speaking at the IDC UK Future of Digital Enterprise Conference, “Building the Future Enterprise: From Digital Transformation to Digital First”. As well as hearing from great minds in the industry, I delivered a keynote on Democratising Data Understanding that I’d love to share with you in case you missed it. Let’s dive straight in…
First things first, by referring to “Data Democratisation”, this means everyone in an organisation has access to data at any time and the ability to use the data for decision making. It sounds pretty logical, sure, but in many businesses we see bottlenecks to accessing and using data effectively. There are two key considerations when it comes to data democratisation; no barriers to access and no barriers to understanding. This could be in the form of data silos preventing analysts from accessing data across the enterprise, or indeed departments using different definitions for the same term. The impact of this can be easy to underestimate.
Let’s talk about removing barriers when it comes to the understanding of data that flows through your business. At CTS, we’ve recently worked with a large international fashion brand who were experiencing trouble with keeping track of what customers were buying across their stores. With a high volume of products across multiple global locations, and each location using different reporting methods, the company couldn’t grasp a firm understanding of their data and were missing a huge opportunity for improvement.
With so many different sources of both internal and external data, the first step is to make all the data available in a data warehouse. This process can be lengthy to achieve but once done, the hard work pays off and our Data Analysts have access to all the data sources – no more silos! Anyone can log into the warehouse, see all the data from your sources and create a report. We’ve democratised data access. So how do we democratise understanding?
As you start scaling your team and becoming more data driven, your analysts will grow accustomed to the data they are working with. At this point, it is crucial to start transforming data into terms your business understands with a unified data model and by defining what every term presented to an analyst actually means.
In the traditional data warehouse structure, it is quite common for each analyst team to have its own data mart. This is another ‘silo’ in which analysts collect a couple of tables they need and define what that data means. This allows specific teams or business areas to access specific lines of data, such as finance or marketing. However, in our modern data warehouse, we want to democratise the understanding of all data for anyone who has access to it – so we layer our approach.
We’ve covered a lot of ground here, so how do you move forward? Firstly, focus on being prepared, things change quickly in business! Remember to use layers to transform your data so it supports future changes by building on the foundations you have instead of reworking every time something changes. With this, only combine sources in the last phases, making it easier to adapt to changes from your suppliers. It’s also important here to make sure you are using terms that make sense to your business, not terms that are coming from your suppliers. And lastly, focus on people. Train your staff from frontline workers up to the C-suite to be data literate and drive change management within your organisation. Only through true collaboration and collective understanding, can you start to open up amazing new opportunities with your data.
At CTS’ Data and Machine Learning division, we focus on delivering innovative data solutions that help businesses grow by making smarter and quicker data driven decisions. Get in touch today if you’d like to learn more.