Do you need ever more data about your customers, competitors or whatever you want to track, analyze and turn into actionable intelligence? There are is a lot of data, Big Data, and gathering or accessing it isn’t a problem anymore.
How do you transform raw data into real business value? That’s the perennial question facing BI stakeholders everywhere.
However, how do you find business value in big data? Simply put: what data do we need to create customer or business value?
Finding the business value in big data is a big challenge. It was already one of the key takeaways of Computerworld’s BI & Analytics Perspectives event. How do you convert big data to business growth with an obvious key role for anything analytics and data visualization?
Extracting big data value: big business gaps
Several IT managers at the event felt frustrated because they have so many solutions to take advantage of big data but lack the resources and ideas on what to do with this data once they gathered it using all the solutions and technologies they have to do so. Many IT managers feel lost in an ocean of big data. The challenge isn’t new, yet it continues to persist.
There is a gap between the possibilities of big data and the ways it is are turned into business value. Furthermore, there is a gap between what IT managers understand and what business leaders understand about the possibilities of big data.
It is a challenge we have heard before in the history of technology and maybe history repeats itself but we can also learn from it: the many gaps in perceptions, possibilities and realities.
The (big) data value questions to ask
IT has never been more important in business than today. The alignment of business objectives and the goals of the IT department is one of the major challenges and data plays a crucial role in it.
It’s up to all of us to translate the possibilities of data into actual value, actionable intelligence, purpose and/or societal improvement. That’s what big data is about. However, it’s not something you will find in the ‘big’ or ‘volume’ aspect of big data (except in very specific applications where the analysis of really large volumes is an intrinsic aspect of the value that is sought, for instance in huge scientific projects). Otherwise, there is no value in big.
In the end businesses will realize this and steer away from big data, looking at their goals, projects and the data and analytics which they need with a focus on these projects and objectives.
It will be about fast data for the Internet of Things and/or which are needed to become a truly customer-driven organization in a real-time world, smart data whereby the focus is on context and purpose and most of all the essential question of the right data at the right time for the right reasons.
The ability for an organization to compete effectively and to demonstrate agility in responding to market opportunities and demand rests largely on making intelligent and informed decisions at the speed of thought (John Amato, Computerworld)
The first question is how much and which data we need to achieve what we want and generate value from big data. The second one is about how we serve customers and business purposes using the exact data we need while ensuring trust because with big data doesn’t just come big challenge and, indeed big possibilities, but ultimately also big responsibility and making sure we don’t drown in the volume but focus on the purpose, big results and outcomes and also small data in a context of people.
It requires a capability and business perspective whereby the “big” becomes the “right” and big data Value becomes a crucial V in the traditional set of the Vs of big data – and data overall.
Top image: Shutterstock – Copyright: Bruce Rolff
This article was also posted in a shorter version on the BT Let’s Talk blog .