A bad workman always blames his tools, or so the saying goes. And while we’ve all been tempted to excuse poorly built flat-pack furniture by unfairly blaming a cheap screwdriver, there is a lot of truth in the idea that a good, finished product requires the right tools for the job. When organisations seek to build an effective data strategy, it is important they have the right framework and the right people for the job; but it’s also crucial businesses understand that to get the most out of their data, they need the right tools and processes in place.
The right data architecture can unlock data assets for the whole organisation to use. (Photo by Nikkikii/Shutterstock)
It might seem obvious to those of us in the data industry, but many organisations still don’t appreciate that data underpins any business metrics. Everything from sales forecasts to capacity planning and analysis of new business opportunities comes from the collection of data, but many data-enabled businesses fail to verify exactly where that data is coming from. This can lead to poor data-based recommendations and strategies. Building a business model on the back of bad data is like building a house of cards: the final product might look impressive at first, but you’ll soon find out that the whole thing will come crashing down with the slightest pressure.
Big data analytics, and the invaluable information a business gains from it, is therefore only as good as the data it is built on; you get out what you put in. When discussing how best to use metrics within a business, I always recommend that they choose data points which are both easy to measure and that ultimately matter to the business. If an organisation gets its data foundations right, it will have access to powerful information that can transform its operations and business model for the better.
What is data architecture?
So, how do businesses ensure they’re getting the most out of their good quality data? It’s all about having the right data architecture. The data that an organisation collects, from sales information to competitor ad spend or market value, has to be able to flow through an organisation to help all aspects of that business. There’s absolutely no point in collecting and analysing the right data, only for the information to be hidden away in a siloed data department, or for it only to be used to benefit specific departments. The right data architecture is instrumental in opening up an organisation’s data journey and allowing information to transform business practices.
But what exactly is data architecture, and how can organisations ensure they have the right data architecture for them? At its simplest, data architecture is a collection of data guidelines, best practice, business culture and, of course, data infrastructure all rolled into one. Good data architecture draws on best practice strategies and analytics methods to ensure that any data collected is being utilised as efficiently as possible.
At its simplest, data architecture is a collection of data guidelines, best practice, business culture and, of course, data infrastructure all rolled into one.
What it is not is simply technology, and this is where many organisations become stuck. For a very long time, data has been seen as the remit of the chief information officer (CIO), with the CIO position often seen as interchangeable with the chief data officer (CDO). While the two roles have grown up together, they fulfil very different tasks. Good data utilisation, and getting the most out of a CDO, is about more than simply keeping up with the latest IT trends.
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The best analogy to explain the difference between CIOs and CDOs is to look at data like a bucket of water. The CIO is in charge of the bucket, or the systems used to store the data, while the CDO is in charge of the water, or the data itself. For an organisation to get the most out of its data, the two roles need to work together to unlock the full potential of the different tools and operations that are available to a business with a good data foundation.
A bad workman may blame his tools, but with data as with DIY, you’ll struggle to do a good job without the right tools and processes at your disposal.
