Businesses will find it hard to fully leverage the potential of data and its related technologies without robust data automation, writes Rob Mellor, VP and GM of WhereScape EMEA
According to the 2019 Gartner fourth annual Chief Data Officer (CDO) Survey, the implementation of a data and analytics strategy was ranked the third most-critical success factor when it comes to a CDO’s organisation.
When it comes to data, we’re all aware of the four ‘Vs’ – variety, velocity, veracity and volume – yet for many organisations, their data warehousing infrastructure is no longer equipped to handle them. Additionally, value, the fifth ‘V’, is even more elusive. So, taking into account the scale of data that many modern companies have means that meeting these challenges requires a new approach – with automation being the foundation.
45 percent of a CDO’s time is spent looking at methods of using data for value creation and revenue generation. This means being able to harness data in a way that is realistic, practical, and actually beneficial. The data warehouse can help meet these expectations, providing enterprise data with a centralised space that business users, the CDO included, can use to develop insights.
For the CDO to succeed in monetising data within the organisation, then, creating a successful data warehouse is crucial.
The traditional waterfall approach to data warehousing that was first introduced in the 1970s, however, only delivers a mere fraction of the value it potentially has to offer.
The approach needs to evolve to address new data sources and adapt to business demands – essentially becoming more responsive as organisational needs change. Using automation software to design, develop, deploy, and operate data warehouses provides a wide-ranging value to business leaders. This change gives flexibility when business needs demand it, and incorporates new data sources and technologies more easily.
What can the CDO do?
The data warehouse is invaluable for providing business users with the information they need, being the central storage point for enterprise data. Yet the gap between user expectations and the data warehouse’s ability to provide up-to-date, consumable data in a timely manner has grown, motivated by users becoming more aware of the potential benefits of data-driven decision making.
Businesses both want and need insights from data a lot faster than before. Additionally, the ever-rising growth of new forms of data intensifies this business need, particularly when it comes to semi- or un-structured information such as client communications, real-time messages, sensor data, social media, and audio/video files.
Customarily, data warehouse development and evolution meant long-cycle IT projects, which contrasted heavily with the needs of more agile project design and build environments. To support digital transformation efforts, CDOs should take the lead in the re-architecting of data warehouses, from creativity to acceleration and automation, in order to increase the business’ time-to-value ratio.