Big Insights from the Big Analytics Roadshow
Last month in New York we completed the fourth and final event in the Big Analytics 2012 roadshow. This series of events shared ideas on practical ways to address the big data challenge in organizations and change the conversation from “technology” to “business value.” In New York alone, 500 people attended from across both business and IT, and we closed out the event with two speaker panels. The data science panel was, in my opinion, one of the most engaging and interesting panels I’ve ever seen at an event like this. The topic was on whether organizations really need a data scientist (and what’s different about the skill set from other analytic professionals). Mike Gualtieri from Forrester Research did a great job leading & prodding the discussion.
Overall, these events were a great way to learn and network. The events had great speakers from cutting-edge companies, universities, and industry thought-leaders including LinkedIn, DJ Patil, Barnes & Noble, Razorfish, Gilt Groupe, eBay, Mike Gualtieri from Forrester Research, Wayne Eckerson, and Mohan Sawhney from Kellogg School of Management.
As an aside, I’ve long observed that there has been a historic disconnect between marketing groups and the IT organizations and data warehouses that they support. I noticed this first when I worked at Business Objects where very few reporting applications ever included Web clickstream data. The marketing department always used a separate tool or application like Web Side Story (now part of Adobe) to handle this. There is a bridge being built to connect these worlds – both in terms of technology which can handle web clickstream and other customer interactional data, but also new analytic techniques which make it easier for marketing/business analysts to understand their customers more intimately and better serve them a relevant experience.
We ran a survey at the events, and I wanted to share some top takeaways. The events were split into business and technical tracks with themes of “data science” and “digital marketing.” Thus, the survey data compares the responses from those who were more interested in technology than the business content, so we can compare their responses. The survey data includes responses from 507 people in San Francisco, 322 in Boston, 441 in Chicago, and 894 in New York City for a total of 2164 respondents.
You can get the full set of graphs here, but here are a couple of my own observations / conclusions in looking at the data:
1) “Who is talking about big data analytics in your organization?” – IT and Marketing were by far the largest responses with nearly 60% of IT organizations and 43% of marketing departments talking about it. New York had slightly higher # of CIO’s and CEO’s talking about big data at 23 and 21%, respectively
2) “Where is big data analytics in your company?” – Across all cities, “customer interactions in Web/social/mobile” was 62% – the biggest area of big data analytics. With all the hype around machine/sensor data, it was surprisingly only being discussed in 20% of organizations. Since web servers and mobile devices are machines, it would have been interesting to see how the “machine generated data” responses would have been if we had taken the more specific example of customer interactions away
3) This chart is a more detailed breakdown of the areas where big data analytics is found, broken down by city. NYC has a few more “other.” Some of the “other” answers in NYC included:
- Client Data Cloud
- Development, and Data Center Systems
- Customer Solutions
- Data Protection
- Financial Transaction
- Healthcare Data
- Investment Research
- Market Data
- Predictive Analytics (sales and servicing)
- Risk Management/Analytics
4) “What are the greatest big analytics application opportunities for businesses today? – on average, general “data discovery or data science” was highest at 72%, with “digital marketing optimization” as second with just under 60% of respondents. In New York, “fraud detection and prevention” at 39% was slightly higher than in other cities, perhaps tied to the number of financial institutions in attendance.
In summary, there are lots of applications for big data analytics, but having a discovery platform that supports iterative exploration of ALL types of data and can support both business/marketing analysts as well as savvy data scientists is important. The divide between business groups like marketing and IT is closing. Marketers are more technically savvy and the most demanding for analytic solutions which can harness the deluge of customer interaction data. They need to partner closely with IT to architect the right solutions which tackle “big analytics” and provide the right toolsets to give the self-service access to this information without always requiring developer or IT support.
We are planning to sponsor the Big Analytics roadshow again in 2013 and take it international, as well. If you attended the event and have feedback or requests for topics, please let us know. I hear that there will be a “call for papers” going out soon. You can view the speaker bios & presentations from the Big Analytics 2012 events for ideas.