Can Cloud-Aware Analytics Make the Difference Between Thrashing and Thriving?
Some organizations might be surviving the current economic hard times in part because they know how to use data better than their failing competitors. Can they extend their lead in good times with new cloud-aware analytics?
By John Santaferraro
As enterprises dig out from the wreckage of the damaged global economy, a surprising fact is emerging: many of the survivors know how to use analytics and data sources better than their competitors. Now, these firms are turning their sights toward a new data exploitation target: cloud-aware analytics.
"Better business analytics had a direct effect on wealth in the recent economic downturn," says Shawn Rogers, analyst and vice president of research for business intelligence and data warehousing at Enterprise Management Associates, a leading industry analyst and consulting firm that specializes in IT and management technologies.
"Knowing how to use the cloud and data analytics better -- either to increase their margins by optimizing their supply chain management or by serving customers better with smarter analytics -- pulled them through the recession. Now they're looking around and asking themselves, 'What else can we do?'" Rogers says.
Cloud-Aware Analytics: New Challenges, New Opportunities
Many of these data-savvy companies are extending their knowledge advantage with "cloud-aware analytics," an emerging practice that combines traditional analytics -- such as the analysis and decision-support software that most enterprises now use for mining their in-house data -- with analytic services offered in the cloud by application providers and information service providers.
For example, sales opportunity assessment information -- such as that provided by Salesforce.com, Eloqua, Marketo, and SugarCRM -- is now being combined with cloud-collected information such as LinkedIn Analytics or Microstrategy's Wisdom Analytics for Facebook.
The result is the ability to make associations among leads, traffic, advertising, and sales -- and to predict which prospects will eventually buy. Cloud-aware analytics could also follow a chain of events and the resulting online social chatter to understand which promotions and ads are likely to generate the kind of social "buzz" that actually moves products.
These cloud-aware analytics, in other words, could be the long sought-after Holy Grail for salespeople and marketers, and could help to eliminate much of previously wasted time chasing prospects that were probably never likely to buy, no matter the deals offered.
"We're just at the beginning of this trend, but the vision is really heady," says Rogers. "The most thoughtful and valuable analytics come from a more sophisticated approach -- and call for inclusion of data from a variety of sources and streams, including the cloud. The companies that can bring all these sources of data together on a single platform, analyze it, and get good answers quickly are going to be the ones that profit as this trend intensifies."
Already, says Rogers, companies are starting to mix different sources of data -- historical sales, customer data, social feeds (such as Twitter), and details about retail products -- integrating it with application data from specific supply chain apps to optimize supply chains and figure out how to stock stores. That goes way beyond running a report from your own store data to see what sold last month.
Companies that are the first to adopt cloud-aware practices will discover new combinations of analytics that give them a clear, competitive advantage, quickly distribute analytics to more business decision makers, and perhaps even become analytics providers in their own markets.
These companies realize that to be competitive, they must have a good data strategy, matching data and workload with tools that can tell them who was served, how fast, and what their customers want -- or could be enticed -- to buy.
Swimming in the Common Data Pool
Smart, sophisticated, innovative companies are taking their data analytics seriously. They know that even if they're all going to be using some common sources of data, the winners will be those that can leverage analytics that keep up with the speed at which they're making decisions.
Some organizations are already learning how to exploit common data for cloud-aware analytics. For example, Autometrics pulls in more than 1,000,000 data points from hundreds of sources every night. It uses cloud-aware analytics to predict near-term auto sales or assess the effect of advertising on sales, and it sells this service to dealerships and others with a stake in motor vehicle sales.
Commercial firms aren't alone in wanting to run analytics on a combined pool of their own information and commonly available data streams. Greek government officials recently discovered that when you fish in the common data pool, you never know what you're going to pull out. Government officials had been authorizing helicopters to fly over Athens to count swimming pools -- a strategy that led to a €13 billion estimate of tax evasion in the cash-strapped country. However, helicopter flights are expensive, so now the government is turning to Google Maps data, combined with tax-return information and other sources to flag likely tax cheats for follow-up and possible enforcement action.
Opening Up the APIs
One of the many implications to this new data mining frontier is a move away from data silos toward more open platforms and greater standardization, says John McCawley, CEO of VereCloud, a cloud services provider and makers of CloudWrangler.
"There's been very little standardization in the cloud space so far," says McCawley. "So we still see a lot of data being wasted. We need greater standardization and better openness, such as more APIs that allow analytics and cloud service providers to connect to data and services that are already available."
For example, says McCawley, in the unified communications space, it's common to specify that after three rings, calls go into voicemail boxes, which typically have size limits that can be exceeded by too many messages. "If my phone is always going into voicemail, that information can be used to send e-mail that I'm about ready to go over my limit, or maybe even to sell a more expensive option or package," says McCawley.
So far, though, "Cloud service providers are still lagging very far behind what we've seen in telecommunications," McCawley explains, noting that better use of cloud data -- and the emerging use of the insights that cloud-aware analytics could provide -- will eventually result in whole new classes of applications and business models.
McCawley likens the situation to the seemingly explosive proliferation of location-aware services that was actually years in the making. "We had geo-location data available for five or six years before we saw many applications that could exploit that kind of data well," he says.
Preparing for a New Cloud Analytics Era
Still in its infancy is the use of cloud-aware analytics that are capable of tapping into cloud data just as effectively and easily as today's BI software analyzes data from traditional in-house sources.
As aggregators such as Verecloud lead the way to standardize business applications in the cloud, there is an open door for companies who seize the opportunity to provide common access to the data behind those applications. Companies that utilize cloud big data for analytics will rise above their competitors.
John Santaferraro is vice president of solutions and product marketing at ParAccel and is responsible for product and solution strategy, communications, and customer relations. Prior to ParAccel, John co-founded a data warehouse software company, founded a consulting company, and held executive positions in companies including Hewlett Packard, Tandem Computers, and Compaq Computers. You can reach him at firstname.lastname@example.org.