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Data mashup tools boost business intelligence, analytics efforts

Customer data can be valuable on its own, but when it's combined with other internal information and outside sources in a data mashup, the business benefits of analytics apps can skyrocket.

The enterprise data warehouse has more and more company as a go-to source of data these days. While straightforward business intelligence and reporting applications often rely almost exclusively on data warehouses, new BI and data discovery tools are making it easier for users to pull data from multiple systems and combine the information for analysis -- for example, in the form of a data mashup that mixes both internal and external data.

The ability to combine multiple data sources and analyze them collectively isn't an entirely new thing. But in the past, it took a lot of leg work by IT departments to build or implement connectors and make sure specific data stores were properly feeding BI and analytics applications. Today, a new breed of self-service BI tools from a variety of vendors has simplified the process. In many cases, new data sources can be pulled into an application through point-and-click interfaces, obviating the need for any deep technical expertise.

At Swiss Farms, a chain of drive-through grocery stores in the Philadelphia area, most of the company's analytics activities relate to tracking sales and purchasing information. It uses a tool from BI software vendor Targit A/S that enables the analytics team to visualize ERP data and publish visualizations either within the tool or to a Web portal. They can also combine that data with info from other internal systems, like the chain's customer service database, or from external sources, including financial data provider Quandl.

Better use of data, better analytics

Chris Gray, IT director at Swiss Farms, said call center data from the customer service database, as well as much of the information in the company's other data stores, went unused in the past. Swiss Farms added the capability to combine data sources via the Targit software five years ago; only since then has it been able to effectively analyze data and generate valuable insights into business operations, according to Gray.

"Data that was just laying around in spreadsheets before, we're now dispersing it throughout the organization," he said.

The next step for Swiss Farms is to add social media data sets to its analyses. Gray, who currently handles the bulk of the company's analytics needs while it looks to fill out the analytics team with two more staff members, said he has already begun looking at Twitter data to deepen his understanding of customer satisfaction and is planning to add data from Facebook in the future. Mashing up those data sets with internal customer call center data is the ultimate goal, he noted. Acknowledging the customers' voices however they choose to express themselves could build a more accurate picture of how satisfied people are with the service Swiss Farms provides.

There are potential downsides to giving business users the ability to blend different data sets themselves with self-service tools. For example, they might pull in untrustworthy data or try to create a data mashup from incompatible or unrelated sources. That's why some businesses are sticking to narrow, focused projects that have a better chance of success than more open-ended analytics initiatives do.

For Pegasystems Inc., a business process management software vendor in Cambridge, Mass., improving its sales leads means boosting the quality of its data through the addition of information from outside sources. To accomplish that, it partnered with outside data provider Avention, which offers information on the staffing numbers, growth rate and market capitalization of various businesses. Pegasystems uses the data to help guide its sales activities.

Mashups help users fill in data holes

Joseph Santos, senior manager for marketing data and analytics at Pegasystems, said the information from Avention becomes particularly valuable when it's combined with the company's own internal data. The combination allows sales teams, which primarily use Tableau as a front-end visualization tool, to validate their own data and fill in holes in customer records.

"You're now closer to your 360-degree view of the customer," Santos said. "We're not going into situations blindly. We already know what the company is doing prior to us talking to them."

Knowing your customers and understanding them at a deep level is the most important aspect of running any business, Santos thinks. It's also one of the most challenging. Organizations typically have a large amount of data about their customers, but in a lot of cases, that's not enough on its own. One of the promises of big data is the ability to reconcile internal sources of information with external, allowing businesses to verify and deepen their data, Santos said.

"What big data means is just a collection of disparate data, whether in a traditional format or free text format," he said. "It's the ability to mine those sources. Without that guiding light, it would be difficult to ascertain what the truth is."

Ed Burns is site editor of SearchBusinessAnalytics. Email him at [email protected] and follow him on Twitter: @EdBurnsTT.

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