During my first few days at EMC, I was eagerly waiting to meet that one person who could tell me something about Big Data that I already didn’t know. I kept hearing verbose, repetitive concepts like “Big Data is the about Volume, Velocity, and Variety” or “Big Data allows you to harness information for competitive advantage” I wanted something more unique, meaningful and tangible.
Enter Bill Schmarzo.
I like to call him Bill ‘Smart’zo and he is the CTO of Enterprise Information Management and Analytic Service line at EMC. Bill is my personal Big Data Hero because he saved me from the unwanted noise and gave me the meaningful information I was seeking. Oh the Big Data irony!
I interviewed Bill Schmarzo to capture and share with you the nuggets of information I gained from a sea of high speed, diverse Big Data conversations.
You work with organizations in developing Big Data solutions that solve real business problems. What is the biggest misconception these organizations have when it comes to implementing a Big Data solution?
The biggest misconception is that Big Data requires a rip and replace approach. I get questions such as “Is all this Big Data stuff going to replace my BI/Data Warehouse environment? Should I be looking to just throw away everything I’ve got? Do I have to start from scratch?” The answer is really kind of in between. You’re not going to throw away your BI/DW, but you do have to look seriously at how you’re going to leverage Big Data technology to complement what you already have in-house. So you’re not going to throw away existing BI/DW investments, but at the same time, you can’t sit around and do nothing.
Many companies have not only heavily invested in BI/DW technologies, but also people. How can organizations leverage their BI people for Big Data?
I’ve been doing BI/DW since 1984 and had that same question myself. So I attended the EMC Big Data and Data Scientist Certification. What I found is that BI people already have valuable skills that can be leveraged. BI people not only understand business metrics, but also have the ability to interact with the business, which is key to success. BI people just need to upgrade their skill sets by learning some new technologies (R, Hadoop). These new skills, coupled with their existing BI and data warehouse skills, will enable them to mine these vast amounts of data for nuggets of insights, and then surface those insights back up into a user’s dashboard and operational environment so they’re actionable.
Which Lines of Business or business functions have gained the most traction in Big Data adoption?
In the B2C space, customer-facing areas like sales and marketing are taking social media data and integrating it with their CRM systems to improve customer acquisition, customer maturity, and customer retention. The second area is around the operational side where organizations with networks of ATMs, kiosks, branches, stores, meters, wind turbines, etc. can leverage Big Data to improve network utilization, capacity planning, predictive maintenance, and fraud detection.
So let me give you an example of a bank that uses social media data to improve customer acquisition, retention, and maturation. This bank has a brokerage firm so the bank’s customers are the brokers who are servicing clients like you and me. The bank’s key business challenge is retaining their brokers since when a broker leaves they tend to take their clients with them. Therefore, the bank has to make sure that they’re doing everything possible to make their brokers successful.
First, the bank expects to help brokers optimize upsell/cross sell opportunities by leveraging social media to understand more about customers and their interests. For example, let’s say I am a broker monitoring a customer’s Facebook news feed and the customer posts that his daughter just got engaged. The broker concludes that the customer will have a major financial event in the next year and can take action by offering the customer a relevant product or service that will help with the event.
Second, the bank expects a 20X improvement with customer acquisition via improved targeting by knowing the Facebook friends of high value customers and leveraging cohorts analysis.
Last, the bank hopes to identify “white spaces” in the market by using social media to monitor customer sentiment and market trends across Facebook, LinkedIn, Twitter, Foursquare, etc. Recently when the markets collapsed, customers were using Facebook and Twitter to complain about their 401k programs. The bank can now identify these unhappy customers more quickly and offer an alternative financial product/service.
What was their key to success?
Where I see companies being successful is when they really have a focus on a business problem they’re trying to solve, and then they take a look at the data that’s available to them and the technologies out there to solve the business problem and drive competitive advantage. And from the bank example I just talked about, nothing breeds success like success. Big Data success requires organizations to target something meaningful to the business, have success, and the next thing you know, there viral interest and firepower in the organization, and you can see people all of a sudden being drawn to it like a magnet.
These companies that have a business focus are further down the path than those that have taken this big data thing and thrown it into some lab somewhere and are “playing” with it. In fact, those organizations are in real trouble of learning this technology and then coming back to the business and saying, look what I’ve got. The business looks at them like they’ve got lobsters crawling out of their ears and respond with “why should I care about that?”
Can you recommend a practical approach to getting started with Big Data?
If you know what business problem you’re trying to solve, start with Greenplum Analytics Lab. This service brings Greenplum Data Scientists into your organization to help you start getting insights immediately into your data.
If you don’t know where to start or haven’t identified a business problem yet, I recommend starting with the EMC Vision Workshop to help identify not only a business problem that they can go after, but also to help them envision where and how big data and advanced analytics can do for that particular business initiative. For example, what does having access to detailed data on a low-latency basis allow me to do that I can’t do today?
The third offering we have is the EMC Big Data Advisory Service for companies who are trying to look across their entire enterprise information management architecture and to assess their level of organizational readiness for Big Data – What’s their current state? What’s their desired future state? And how are you going to get there?
Thank you Bill for the nuggets of valuable information. You can follow Bill through the Infocus Blog and through Twitter at @schmarzo
And now to my readers…who wants to get started with Big Data?