Moving data and analytics to the cloud can be a challenge. Given their variety, there’s no one-size-fit-all approach. Still, the immense benefits of the cloud outweigh those challenges, concluded a recent panel on cloud analytics at the Hotel Zetta in San Francisco.
— Sammy Totah (@SammyTpr) July 29, 2015
Doug Henschen, an analyst at Constellation Research Inc., moderated the panel featuring Adam Hall of Google, Brad Peters of Birst, Arsalan Tavakoli of Databricks, Tor Stahl of Practice Fusion, and Tableau’s own Ellie Fields and Ashley Jaschke. The 90-minute discussion covered a range of topics including unfortunate evolution of the term “Big Data” (the panel’s conclusion: if you can’t beat’em, join’em). Here are three key takeaways from the panel on transitioning to the cloud.
A fundamental benefit of going cloud, said Tor from Practice Fusion, is that you don’t have to maintain a server. Cloud also keeps you secure while allowing you to stay flexible to scale quickly and embrace business opportunities.
Practice Fusion, a healthcare startup, used Tableau Online to build a tool that compares the effectiveness of drugs. The analysis itself is straightforward, but sharing the data with the company’s pharmaceutical customers has proven invaluable. Therein lies the beauty of the cloud, added Ellie.
"This pattern is commonly found in organizations that need to share and collaborate with data outside of the firewall, or when they want to enable mobile scenarios, like a field sales team,” Ellie said.
Concerns about cloud security are rapidly becoming a thing of the past. Reputable cloud vendors can dedicate more time and resources to managing cloud security than any single enterprise. When vulnerabilities are discovered, for example, a cloud vendor can direct entire teams to immediately test and apply patches.
Most organizations have their data in more than one place. And many embrace a hybrid model of on-premise and cloud data. It’s unrealistic to expect all organizations to go all-cloud—or ever want to do so. Highly sensitive data, like patient records which fall under HIPAA compliance, will always keep some data on-premise.
Those looking to transition to the cloud should first figure out their needs, specifically what type of data they have and how they want to use that data. Then they should partner with a team willing to spend the time to understand and support those specific needs. Large enterprises who want to move all of their data to the cloud must first secure two things, said Brad from Birst: executive buy-in and technical resources. Support is crucial.
When you think about your cloud analytics strategy, it’s important to distinguish data storage from analytics, said Adam from Google. In other words, if you’re trying to kick off your first analytics project in the cloud, don’t try to pull in all of your data and anticipate all future analyses.
"The problem with analytics is you have no idea what questions people will ask,” Adam said.
Instead, define a specific use case and pull in just the relevant data. Put some of your data to work first, then build from there.