Neither the concept of Cloud, nor that of Big Data really need introductions at this point in the Enterprise Game. Cloud is consuming the enterprise across business process, applications and more, while data is the first name of the “data driven Enterprise” and is created to the tune of 2 1/2 quintillion bytes a day, prompting investors to bet the farm on the concept of efficiently mining vast amounts of data to identify unforeseen relationships missed by competitors gathering the same crop to edge the others out.
The symbiotic connection between Cloud and mass Data creates infinite opportunities in the Enterprise, but also a long series of headaches for roles ranging from the (obvious) CIO and CFO to these days even including the COO and CMO.
Data can be farmed to outperform, reign in BPs, avert risk, consolidate systems, increase efficiency, streamline mergers, cut wasteful spending, modernize IT, identify potential markets, boost innovation, on and on... But do you really need all of that data? Who determines what is kept and discarded- or what is the value of what isn’t trimmed vs the cost of storage and backup? Have you seen the cost of the heavy lifting for juggling data of this size? The processing power needed for Enterprise-sized data is Enterprise-priced for on-prem and owned (-even colo) data centers, and then you have to plan, build, manage and scale it all on top of that.
That’s where Enterprise Cloud and the “Back-to-the-Basics” concept of Cloud as a utility come in. Cloud backed by a provider such as Google has the on-demand power, scalability and elasticity needed by the Enterprise on an as-needed basis with wholesale prices. This comes with multiple, redundant, secure data centers managed by the best in the business, and all wrapped into the same price to deliver what the Enterprise really needs: actionable and data-driven business insights.
‘Michael J. Franklin, Professor of Computer Science at UC Berkeley, remarked that [Google’s] BigQuery (internally known as Dremel) leverages “thousands of machines to process data at a scale that is simply jaw-dropping given the current state of the art.”’
Google states that “BigQuery is a web service that lets you do interactive analysis of massive datasets - up to billions of rows. Scalable and easy to use, BigQuery lets developers and businesses tap into powerful data analytics on demand. BigQuery works best for interactive analysis of very large datasets, typically using a small number of very large, append-only tables. For more traditional relational database scenarios, you might consider using Google Cloud SQL instead.”
For some actionable insight into BigQuery, take boo-box as an example. boo-box is an advertising network with clients like Intel, Fiat and Unilever that places 3 billion ads across 350,000 sites on just a monthly basis that uses BigQuery over MySQL and Hadoop to gain all but real-time insights into their business.
White Stratus is leveraging BigQuery to help Enterprise customers in sectors like retail to drill in on the who, what, where and why of their customers- live, as it happens, improving supply chains and streamlining their teams. And this is just the tip of the iceberg when it comes to the possibilities laid out by the powerful combo of Cloud and Big Data for the Enterprise.
If you would like to hear more about Cloud, Big Data, Google or BigQuery for the Enterprise please contact email@example.com