In one of Charles Dickens’ novels, a young English orphan boy named Pip received a large sum of money from an unknown benefactor and was told he would go to London and learn how to become a “gentleman.” Charles Dickens entitled his novel “Great Expectations”, describing how Pip felt on his way to the metropolis of London. In classic Dickens’ style, things are never what they seem and Pip’s fortune does not lead to a life of comfort and ease.
The theme of Great Expectations came up in a number of different ways on my recent trip to the metropolis of New York City to attend and present at the Big Data Summit organized by CDM Media. The presenters and delegates were a ‘who’s who’ assembly of people whose titles begin with the letter C: CIOs, CTOs, CDOs (Chief Data Officer), and even a CAO (Chief Analytics Officer), from some very well-known enterprises and brands, including American Express, Citi, AIG, Allstate, Suncor, and the National Basketball Association.
I certainly had great expectations going to the event: surely the industry luminaries would have Big Data all figured out and I would be able to come away with a better understanding of Big Data use cases. The first speaker heightened my expectations – he gave jaw-dropping statistics about how Big Data helps the healthcare industry fight the annual loss of two hundred billion dollars to fraud and how Big Data helps a wind energy company optimally place its wind turbines by crunching massive amounts of weather data.
Another speaker gave an impassioned call to train our schoolchildren in technology and mathematics so they could become data scientists, helping corporations and nations gain a competitive edge.
Three surprising commonalities came out of these presentations and nearly 20 private conversations with these executives:
- They don’t have Big Data all figured out. Successful projects with large ROI are few and far in between, many are still in the experimental phase.
- Adoption is low. One executive said, “My problem is getting my people to actually use the expensive data warehouse we bought.” His data warehouse had over 125 terabytes of data.
- Innovation comes from data mashups. The executives were most excited about the possibilities when internal data is combined with customer data, sensor data, and news feeds to deliver new services that don’t currently exist.
What did exceed my expectations was the high level of engagement the executives had as they learned about QlikView in relation to Big Data. The top reasons were:
- QlikView helps them walk before they run. When asked if they are making the most use of their existing “small data,” not one person said yes. They saw how QlikView’s Business Discovery platform helps them achieve immediate return on the data they have, rather than waiting years for their Big Data projects to complete.
- QlikView helps them explore their Big Data. Because creating data mashups is so intuitive and simple in QlikView, they can take extracts from their Big Data source, mash them up with other data sources, and explore the results in real time without the usual query lag and laborious data modeling work.
- QlikView reduces dependence on data scientists. Everyone who saw a demo of QlikView for the first time was impressed with how intuitive it was to answer question after question simply by clicking, without having to create more visualizations or hire data scientists to do so. Since QlikView can scale from “small data” to Big Data, it uniquely addressed their short and long term analytic needs.
Like a great novel with unexpected plot twists, I entered the conference with great expectations, saw them brought low, but then ended with a fresh excitement over what QlikView can do for the largest of enterprises wrestling with the challenges of getting broad value from both small and big data.
For more information, check out QlikView’s page on what Big Data can do for you.