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There’s a lot of rich data being gathered within most companies these days, but taking that data, thoroughly analyzing it, and turning it into actionable insights…well, that’s where some real business gets done. Take a listen to how some analytics experts are mining every possible gem from their data warehouses — and how you can leverage those BI strategies to pull more from your data diving. 

Missed it? Access this VB Live event on demand right here.

Imagine for a minute that your network infrastructure was designed so that each department in your company had its own separate network, with none of them interconnected. Any effort to share between departments required a thumb-drive “sneakernet” delivery of files or intraoffice e-mail — inefficient and rife with coordination problems at a time when departments need to be able to collaborate without wasting time.

You may laugh that this connectivity hypothetical was in fact your company’s reality 20 years ago, but thankfully it’s not the case in 2016. However, if you consider your company’s current data-collection efforts, then you might conclude that you’re mis-handling your data and unnecessarily isolating departments from each other at a time when they need to be able to collaborate on analytics without wasting time.

A big problem for Robert Olson, Director of Data and Analytics at cloud-infrastructure provider DigitalOcean, was that his company had been set up so each department — platform, network, datacenter, supply chain, and others — was analyzing its specific data independently. Olson explains to Evan Schuman, moderator of a recent VB Live evnt on the evolution of today’s analytics, that each had its own reporting tools, unique ways of defining metrics, and specific terminology and definitions, which became confusing and time-consuming when departments needed to put their heads (and analytical findings) together.

“We ran into this distributed analysis challenge,” Olson says, where each group was using its particular data and “building a different, sort of siloed context of the business. Then we’d come together and have a challenge trying to incorporate all of that data into what the bigger story was and how we can make bigger changes to the entire operation rather than minor, granular changes within a certain function.”

Having the departments (and their respective data) isolated from each other made it hard to test new hypotheses, left the teams unable to ask and answer cross-functional questions, and prevented them from coming to a shared understanding of how the data interconnected between departments. Switching to a centralized data model brought big payoffs.

“When you succeed at centralizing and connecting that data, and getting people a broader overview of the data that impacts the broad, overarching goal for the business,’ Olson says, “it makes it a lot easier to test hypotheses that span business groups, [such as] ‘If we acquire more customers in this country, how is that going to affect the lead time for our supply chain out of this distributor?’ It’s different types of data all getting connected together.”

“It also is really beneficial in that, different people throughout the business are immersed in this connected data, and that builds the context for people who used to live in silos. They start learning about how the data they’re generating, the data they’re looking at, connects to different parts of the business, and that just builds this rich context and makes our discussions and planning a lot more rich.”

Making a radical change to how your company handles its data — along with a commitment to headcount and software packages that may be needed to better draw actionable insights from the analytics — requires buy-in from the C-suite. But Olson thinks it’s easy to assure the higher-ups that such a move will highlight new revenue opportunities that maybe weren’t envisioned through the current processes.

“One of the most powerful things to point to — especially something that a CFO can relate to — is that you’ll have consistency in the lens with which you evaluate the business,” he explains. “It builds trust across the business. You can go to any of the C-levels and start a conversation about developing talent throughout the organization through developing this broader, more rich business context.”

“Do you really want the people who are in the most technical fields not exposed to your business-acquisition metrics and your financial metrics, your user acquisition? I think that’s where startups…have been leading the way in pushing companies toward data democracy and allowing people in any function to learn and be exposed to data in other functions.”

Olsen was joined by Ross Bixler, (Director of Business Operations for financial-services company Underground Elephant), Andrew Searson (Director of Analytics at business-intelligence firm Looker Data Sciences), Jon Cifuentes (Analyst at VentureBeat). You’ll want to hear all of their valuable analytics perspectives – check out this essential VB Live event on demand now.

Don’t miss out!

Access this VB Live event on demand for free right here.

This VB Live event will teach you how to:

  • Utilize analytics to root out inefficiency
  • Turn analytics into actionable insights
  • Move from data theory to insight practice
  • Take data from the abstract to the concrete
  • Identify and solve problems faster and more efficiently


  • Ross Bixler, Director of Business Operations, Underground Elephant
  • Robert Olson, Director of Data and Analytics, DigitalOcean
  • Andrew Searson, Director of Analytics, Looker
  • Jon Cifuentes, Analyst, VentureBeat
  • Evan Schuman, Moderator, VentureBeat

This webinar is sponsored by Looker.



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