PODCAST Episode.01
Harnham rocks!

The value that data analysis can provide to organisations is becoming increasingly clear. But with all the buzz around the endless ways that data can be used to revolutionise your business processes, it can be overwhelming to know where to start.

Fundamentally, what you can do with your data and how useful it may be will hinge on its quality. This is the case no matter what data you may have, whether that be customer demographics or manufacturing inventories.

High-quality data is also imperative for utilising exciting and innovative new technology such as Machine Learning and AI. It’s all very well investing in tech to harness your data assets to, for example, better inform decision making, but you won’t be able to glean any useful analysis if the data is full of gaps and inconsistencies.

Many will be looking at this new tech and be tempted to run before they can walk. But building quality data sets and water-tight, long-lasting processes will form the foundation for any future developments and should not be overlooked. This is where Data Governance comes into its own.

Data Governance (DG) is an effective step in improving your data and turning it into an invaluable asset. It has numerous definitions but according to Data Governance Institute (DGI), “Data Governance is the exercise of decision-making and authority for data-related matters.“

Essentially DG is the process of managing data during its life cycle. It ensures the availability, useability, integrity and security of your data, based on internal data standards and policies that control data usage.

Good data governance is critical to success and is becoming increasingly more so as organisations face new data privacy regulations and rely on data analytics to help optimise operations and drive business decision-making.

As Ted Friedman from Gartner said: ‘Data is useful. High-quality, well-understood, auditable data is priceless.’