The surge in the amount of data available for businesses across all industries has led to the emergence of a relatively new but extremely important strategy: implementing data governance.
Organisations that want to get the most out of their data analytics programs now see the need to use data governance. Simply put, it’s a way of establishing consistent rules and processes for the collection and analysis of data.
Part of what drives the need for better data governance is the sheer complexity of current information systems. Most organisations aren’t dealing with a single data warehouse. Instead, they handle data from multiple sources, all of which need to be analysed properly to power operational intelligence.
The diversity of information has created a situation where a governance plan is necessary to understand the details of each data process flow, as well as assure both the validity of data sources and the security of information.
Data governance is separate from data management. The latter provides plenty of challenges by itself, with the need to manage both data storage and the sharing of data across multiple platforms, to name just two vital areas.
But governance goes beyond this. It establishes control and authority over how the various areas of data management will be handled. This typically requires a shared vision with input from people in all departments that touch the data management process.
Some of the areas a data governance plan would oversee include:
It’s a widespread effort. But creating a shared plan that establishes strong parameters and consistent rules for the handling of data is necessary with so many people involved. Otherwise you get a situation where data is “siloed” in different departments and everyone is running operations off their own game plan.
In general, data governance involves these fundamental issues:
In many ways, it’s still early days of data practices in general. Many companies are deep into data collection. That’s led to accumulation of billions of data points stored on servers but, in many cases, there’s a lack of real insight from that data because it hasn’t been leveraged properly.
Data scientists are in great demand for this very reason. Everyone can collect data and distribute analytics reports with plenty of numbers for people to contemplate. But data scientists and analytics experts are needed to find ways of making use of that information.
Establishing strong data governance is one of the first steps they take to reach that goal.
No two companies are completely alike in how they establish data governance, but there are some key areas to keep in mind.
Innovation and increased sophistication in technical systems has given organisations the tools they need to collect and analyse data. It’s up to the people involved to create a plan for how to best leverage that tool in a way that provides insights into an organisation’s operations.