Data quality and good data governance are important, but is cleaning and verifying data the reason you’re in business? Many enterprises are missing valuable opportunities to turn data into valuable insights through BI and analytics because they’re overly focused on data governance at all costs.
When the number one priority of data solutions is ensuring the data is 100% error free, an organisation can spend years building what’s been called a “data cathedral”. The concept being, in a data cathedral, only the purest of data is included and there is extensive effort in ensuring perfect governance and accuracy.
Meanwhile, stakeholders throughout the organisation are setting up their own informal data marketplaces where they collect and pass on data in spreadsheets. While spreadsheets are great for individual users to keep track of individual projects, they aren’t sufficient for uncovering the insights today’s enterprises need to stay competitive.
Focus on the outcome required
A data solution is not an end in itself. Every department and business function will have goals they want to achieve from data that range from basic reporting to more aspirational analytics. Some of the questions they might have include:
- Who are our most valuable customers?
- Which products and services should we be offering?
- Can we operate our supply chain or operations more efficiently?
- Find out what data you have available
In a digital world, there are very few elements of an enterprise that aren’t collecting data in some format. These datasets might not match the strict requirements set out within the enterprise data governance regime, but they still have value when they’re well integrated into a BI or analytics tool. To be a truly data-driven organisation, it is essential to be asking how every dataset, no matter its perceived quality, can be used to drive decisions and outcomes.
Use an agile approach
As I’ve mentioned previously, using BI and analytics to create a competitive advantage doesn’t happen at the flick of a switch. The best results are achieved by starting small and using short, sharp sprints to actually create business value from previously underutilised data sets. Each of these sprints create an iterative environment where regular stakeholder feedback enables the implementation of BI tools to deliver faster value.
Obviously we still want to be able to trust the information that BI and analytics provide us, but data governance is only one part of the BI implementation process, not the entire process itself. Like every area of enterprise technology, from security to storage and analytics, no one business is likely to be an expert in everything. Rather than wasting time trying to perfect data quality practices, your organisation will gain greater value from data by working with expert technology partners who can help you achieve your data governance and analytics objectives, while you focus on what makes your business great.