How Big Data Is Changing Enterprise Applications
Companies can use in-memory processing and Hadoop to handle Big Data. But how will that change enterprise applications?
There’s no doubt Big Data is changing how companies are able to process and use data. But what’s less discussed is how Big Data technologies, from Hadoop to in-memory processing, are altering the enterprise applications landscape.
“We truly believe that the real value of Big Data will be realized when you build those capabilities into your business processes, your enterprise applications,” said David Jonker, the head of Big Data Strategy at SAP. “While you need a single platform that simplifies your IT environment, because we think that’s fundamental to enabling this, there will be many applications built on top of that, applications that solve very specific problems, so that is our strategy for Big Data at SAP.”
That’s why SAP is now building many of its enterprise applications — including CRM and its widely used ERP solution — on top of the company’s in-memory processing platform, HANA. It also has an analytics solution for business intelligence (BI) that resides on HANA.
While much of the discussion about Big Data focuses on storing and processing large datasets, Jonker said most organizations can handle the volume of data. What really frustrate companies is the speed, or velocity, it takes to process and analyze it.
In-memory processing solves that velocity problem by keeping the data in-memory, rather than storing it on a disk. Building enterprise applications on top of an in-memory platform substantially changes how those work, he explained.
Instead of limiting ERP or CRM data to a three-to-six-month time frame and then off-loading it to a data warehouse, companies will be able to retain historical data in the enterprise application itself, without degrading the application’s performance. It also simplifies the infrastructure needed to support these applications, Jonker said.
“You can run your transactions and your analysis on one system against all the detailed information,” he said. “There’s no need to create all these aggregates or these cubes or all the summary of data. There’s no need to throw data away. You can keep it all there in one system, and so the cost of a solution like this goes down. The overall complexity is greatly simplified with a solution like this.”
SAP has revamped more than 30 of its applications to run on HANA’s in-memory processing platform.
In-memory isn’t the only Big Data technology that’s changing how enterprise applications are built. Start-ups are also using Hadoop, the open source Big Data tool, as a platform for powering new applications, according to Jack Norris, vice president of marketing at MapR Technologies, which offers a Hadoop distribution.
“Some Web 2.0 companies are building the business around Hadoop, with Hadoop as the engine underneath,” Norris said. “Ancestry.com does the whole family relationship matching, and they even have a DNA matching service now. Hadoop is core to that processing.
“So it’s not just taking existing business intelligence or existing data warehouse processing and doing them faster or more cost effectively; it’s really opening up some of these really new possibilities that have a dramatic impact on revenues.”
Xactly is an example of a company using Hadoop to change what’s possible with CRM, he added. It’s a sales compensation management solution, based in the cloud that integrates with Salesforce’s CRM solution.
“They are actually integrating Hadoop into their offering and their focus is to provide additional metrics and analytics to customers,” Norton said.
Even though Big Data solutions are the foundation for new applications and new functions for traditional enterprise applications, that’s not how most organizations start with Big Data, according to Jill Dyché, vice president of Thought Leadership with BI and analytics vendor SAS. In fact, they’re not even necessarily using the data from these applications when they first start Big Data initiatives.
Big Data and CRM
“Can you use ERP as a source for a Big Data project? Yes, absolutely. Is that where people are starting? Absolutely not,” Dyché said.
Typically, organizations use systems like Hadoop to speed up existing processes, such as evaluating credit risk scoring or processing social media data for more targeted marketing, experts say. To that end, a Big Data project may pull from a CRM system. In fact, Dyché explained, it can help companies finally achieve what they’d hoped CRM would do all along: Allow them to better target their existing customers for marketing campaigns.
“What it is possible to do is to have more segments of fewer customers to make the conversation that much more relevant,” she said. “The whole drama around CRM 15 years ago was about, 'At the end of the day, my CRM system is just automating my phone book. It's not necessarily helping me drive insight into specific segments of customers and their specific purchase behaviors and preferences.'
“Now with Big Data we can not only do that, but we can drill down on even more behavioral detail very, very quickly.”
Big Data and Business Intelligence
Big Data is being used most extensively today with business intelligence and analytics applications. BI and analytics vendors have rushed to embrace Hadoop in the past year.
Some companies, including SAS with its SAS High-Performance Analytics Server and IBM with InfoSphere, have launched BI tools built on in-memory or Hadoop platforms. But almost universally, BI tools now support Hadoop in at least one of two ways, Dyché said:
- Integration connectors that make it easier to move data from Hadoop into their tools
- Data visualization tools that make it easier to analyze data from Hadoop
Even SAP, which has gone the in-memory route, recognizes that Hadoop has a place in a Big Data system, and offers connectors to Hadoop for SAP BI and Business Objects.
So, it’s clear Big Data technologies are changing enterprise applications and the systems that support them. But it’s still too early to know how much these technologies will ultimately change how companies use and build enterprise systems.
“The true value of Big Data will be fully realized when yes, we do existing things better, but also when we re-imagine what’s possible,” Jonker said. “The next phase is to say how do we re-imagine what we do so that we can run our businesses in completely new and different kinds of ways? And that’s where a lot of innovation will continue to come.”
Loraine Lawson is a freelance writer specializing in technology and business issues, including integration, healthcare IT, cloud and Big Data. Follow her on Twitter @LoraineLawson.