Tableau: How did you analyze data before Tableau?
Michael: In the very beginning, we have 500 sales people that essentially supported by one poor analyst who's great, but oftentimes the one person would be overwhelmed by a lot of requests from these 500 people.
And then if you do a simple math, like everyone send a request to this person, and then if this analyst can finish three analysis on daily basis, then we're talking about roughly every half year, then one salesperson's question can be answered, right?
It's just not scalable. That's why we decided to focus on how do we scale the solution that we build, really provide the scalability and empower our sales team to get what they need in time. Which is why like over time we build this analytic portal, become a one-stop shop for sales people to get what they need in a very self-serve way, right?
Tableau: How has that changed?
Michael: If you look at the portal we build, internally we call them Merlin, now on a weekly basis, thousand or so people literally visiting the site, it's roughly 80 to 90 percent of sales person using on a weekly basis getting value from it.
Tableau: Where does Tableau fit in?
Michael: Tableau is a key piece of it. So we build essentially a one-stop shop, it's like an internal Web portal that centralize all the analytics that the sales team may need for customer success.
And then we build predict modelings to predict what are the accounts that are more likely to churn. And then, you know, what are the best way to prevent the churn from happening, if you could predict that account is actually at high risk to churn?
Tableau: So how do your analysts work now?
Michael: We have a team of great analysts that we're very proud of that they understand technology and the business. So they will sit with their business partners, sales and marketing partners, really understand what they're doing, you know, what's needed from their side in terms of analytics support and figure out what technology is available to enable that, empower that, to help them optimize their business, and then create better solutions, right?
Tableau: Where are you pulling data from to analyze in Tableau?
Michael: We're talking about we have our internal databases, we have third-party tools, CRM systems used by different teams. And then, essentially, this data is big. This is really, really big data. We're talking about the data can be in petabytes, right, even bigger than that now that as the data continue to grow.
At this point, with the scale of LinkedIn, right now we're more focus on, hey, how do we centralize all the data in our own data warehouse and then build metadata on top of it, build the data governance on top of it? And then use Tableau to build a visualization.
I think right now Tableau is helping a lot on the data visualization side. After we build this curated data layer and Tableau helps a lot in terms of getting data very quickly and generate visualization towards a need from our business partners. And then being able to provide that in a very easy-to-consume way.
Tableau: How do you bring your data into Tableau?
Michael: We build the Tableau dashboard reports on top of relational database, meaning if we do need to get data from Hadoop into Teradata, we actually have a data ETL process in place in the middle—ETL the data to a relational database like Teradata or MySQL or some other common relational databases. Or we migrate the data to more of the newer databases, maybe some of the NoSQL databases as well as Tableau got a data connector to it and build on top of it.
Tableau: So what insights are you gaining?
Michael: Let's say, if the customer has been using the product a lot, right, so that's a high-risk indicator. So then you need to talk with the customers around how you can increase the product engagement for them so that they can find out if the product has value to them or not.
And then sometimes it's dynamic so that different sales team may look at different ways to understand performance at their level so that they have a sense of urgency when things not going well, or they know that they have been doing a good job that they need to keep it up.