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Cloud analytics for organizations.
Data gravity. It’s shifting to the cloud. But what does that actually mean? And more importantly, what does that mean for you and me?
People should always come first. But after that, data is both king and queen of any business. Wherever data goes, so does much of your business—hardware to store it, people to manage it, applications to make sense of it. And as data grows in size, so does its pull—hence, the term data gravity. Dave McCrory first coined the term in a 2010 blog post. That's right, the pull of data is not a new concept.
It makes sense too; an analysis tool is meant to reduce the time between asking a question and getting an answer. So, how do you reduce time to insight when it comes to your data? You create your analysis as close to your data as possible.
Traditionally, all of the business’s data was generated behind its internal firewall—so it made sense that you had a data warehouse, administrators, and analysis tools that also lived within a company’s walls.
That’s simply not true anymore.
Does your business have a social media account? You have external data. What about your website's performance? You have external data. Do you track mobile clickstreams? Do you want to measure consumer sentiment? Do you use external industry data or other third-party research? All of that is external data, and it is probably being generated in the cloud. You get the idea.
External data is only going to become more ubiquitous, not less. Constellation Research estimates that by 2020, 60% of mission critical data will reside outside a business’ walls—that’s more than half of your data generated externally, just three years from now.
Much of that data is being generated and stored in the cloud for the same reasons many technologies are moving to the cloud in the first place: lower overhead, fast startup time, and infinite scalability. And the cloud brings those same advantages to data analysis. Imagine setting up you BI tool, connecting live to Google Analytics, creating a custom dashboard to analyze website traffic, and sharing it with your team—all in a few minutes. When you see the speed at which data generated in the cloud can be analyzed with tools also hosted in the cloud, data gravity begins to make sense.
What’s more, data sources are only going to become more and more diverse—the days of bringing everything into a single data warehouse for analysis are long gone—and your analysis tool should give you the ability to connect to it all, helping you can take advantage of data gravity.
That said, moving to cloud-based BI and analysis tools doesn’t mean jumping in all at once. Remember that data gravity influences the location of analytics. So if your data is stored across cloud and on-premises, your analytics need to provide a hybrid solution that connects to data wherever it lives. Cloud services are there to support your business, not to be an all-or-nothing solution. Many companies today are using a hybrid approach to storage and analysis of on-premises and cloud data for that very reason.
Want to learn more about data gravity? Join Doug Henschen, VP and principal analyst at Constellation Research, Ashley Kramer, Tableau’s director of cloud vision and strategy, and Dan Kogan, Tableau’s Director of Market Intelligence and Analyst Relations, for a webinar discussing the three imperatives for innovating with cloud BI and analytics. You’ll see which organizations are adopting cloud-based BI, and why. You’ll discover how new organizations are delivering insight as a service over the web, and learn how to build an actionable transition plan to take advantage of the cloud.
The location of your analytics is directly related to the time it takes to go from raw data to critical insights. Recognizing that powerful connection is what data gravity is all about.