A CDO’s guide to data warehouse automation: Why it is needed and how to succeed with data

The four “Vs” of data are well known – volume, velocity, variety and veracity. However, data warehousing infrastructure in many organisations is no longer equipped to handle these. The fifth elusive “V” – value – is even more evasive. Meeting these challenges at the scale of data that modern organisations have requires a new approach – and automation is the bedrock. For CDOs, it’s all about finding methods of using data for value creation and revenue generation, which occupies 45% of their time. This means harnessing the growing beast that is data in a way that is practical, manageable and useful.  That’s where the data warehouse comes in, providing a centralised space for enterprise data that business users, including the CDO, can use to derive insights. Creating a successful data warehouse is critical for CDOs to succeed in monetising data within their organisation. However, the traditional waterfall approach to data warehousing, first introduced in the 1970s, delivers only a fraction of the value that it could potentially offer. Instead, the approach needs to evolve to become more responsive as organisational needs change, addressing new data sources and adapting to business demand. As IT departments are expected to do much more with much less, processes need to change. Data warehouses can no longer be created “artisinally” – IT teams need to focus on producing an adaptable decision support infrastructure. Here are five steps for CDOs to help their company achieve this: