1. How big is the Big Data challenge?
The biggest challenge is how soon you need to move. My advice - follow the money, and importantly, follow your competitor’s and your industry’s money. If you can’t see how you can make money out of big data, or how your competitors can stop you making money, then don’t do it yet.
There are obvious benefits of waiting – the software and solutions are very immature and there is not a lot of help out there so many organisations are assuming a lot of integration and success/fail risks. Waiting does however create an obvious problem – can you afford to be wrong or late?
2. What’s the traditional approach to BI?
Traditionally organisations start building high impact analytic solutions that really add value. Over time build lots and lots (and lots) of these until the management and maintenance overhead becomes crippling. A high priced consultant then comes in and tells them they need a data warehouse or something similar with another name. Everything stops while the data infrastructure is built, and by then everyone has forgotten what the pressing problems were.
3. What specific challenges are customers asking you to address?
Customers are investing heavily in data, which is not surprising as the linkage of spend to benefit is very direct. While that is great it has created issues: they now have now multiple data solutions, multiple data silos, multiple transformation silos, and multiple data repositories. Our customers are now asking us to make sense of these complex data landscapes, and if that is not enough, to help them understand what is being used and what is not, and how to avoid over engineering and under engineering data solutions. Not much really!
4. How do you expect these to change over the next 5 years?
Cloud, along with the adoption of big data approaches (as opposed to big data technologies) is shaking up the data space. Data is a late adopter of cloud – not surprising when you consider the size of repositories we deal with, but I expect to see cloud data repositories become the norm.
5. Will this new approach impact the role of the IT department?
Traditionally IT have struggled to keep up with user demands, and now that the business community has some powerful self-service technologies IT are struggling to justify their existence.
They have some big decisions to make. Does IT give up trying to add value and either deliver infrastructure (and why wouldn’t I then just go to the cloud?) or a data lake? Or does IT step up and deliver data at the speed now demanded by the business – while at the same time doing what they have traditionally done well: delivering performance, scalability and governance?
6. How do you know which data is valuable?
It’s all valuable! And big data and cloud have changed the cost equation so we can store more data for longer. But at the same time the cost of people has gone up so automate as much as possible and “follow the money” when picking where to put your efforts.
7. Tell me about the role of Chief Data Officer
Every business is a data business, and organisations that have a Chief Data Officer are making a statement that data is no longer a by-product, it is a core part of their business.
8. Are there any specific use cases you can share?
I see a lot of old use cases delivered in new ways. For every high profile big data/sensor/Internet of Things story you read about there are ten low profile examples of how big data techniques are helping solve every day (and very real) business problems much faster and much cheaper.
9. What advances can we expect to see in the analytics space in the next 12 months?
As self-service and citizen data usage rises, look for more focus on boring topics like metadata and curation. The bad news is that we are at the stage where we need to pay some technical debt back, the good news is that there is some exciting (well exciting as metadata can be!) tech coming to help.