TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Beyond Reporting: InetSoft Thinks Bigger

iSuite boasts canned connectivity into heterogeneous data sources, which lets it support right-time reporting and analysis requirements.

• By Stephen Swoyer
• May 9, 2007

Who says there’s a dearth of business intelligence (BI) or performance management (PM) pure-play vendors? The ranks of the prominent BI pure plays have been whittled down to some extent over the last half-decade, what with acquisitions, incursions from without, and jockeying on the part of the BI and PM powers.

All the same, the BI and PM pure play space continues to thrive. In the dashboard and visualization segments, for example, at least a score of pure play vendors—some upstarts, some proven competitors—lock horns with the likes of Business Objects SA, Cognos Inc., Microsoft Corp., and Oracle Corp.

In the reporting space, too—that most commoditized of market segments (what with incursions from Microsoft and Oracle, along with the development of a viable open source reporting ecosystem, too)—BI pure plays continue to power ahead. Take InetSoft Technology Corp., a venerable provider of reporting, integration, and (more recently) visualization and PM dashboard technologies.

InetSoft first made a name for itself with its Style Report family of Java reporting offerings. In addition to the vanilla Style Report—which InetSoft launched a decade ago—the company markets Style Report Pro, Style Report Enterprise Edition, and Style Report Analytic Edition.

InetSoft has been thinking bigger—a lot bigger, actually—of late. Last month, for example, it unveiled version 9.0 of its InetSuite (iSuite) operational BI suite, an all-in-one reporting and analysis stack that brings together its data exploration, analysis, monitoring, reporting, and collaboration tools. iSuite’s killer feature, InetSoft officials claim, is its canned connectivity into heterogeneous data sources (typically via JDBC), which lets it support right-time reporting and analysis requirements. This makes it a good choice for a number of scenarios—including frequently refreshed reporting, data warehouse modeling, or as a temporary (or "band-aid") solution for organizations preparing to roll out or extend a data warehouse. There are even scenarios in which iSuite can function as a complement to established enterprise data warehouses, officials claim.

"iSuite is really comprised of three different pieces," says Alan Stern, vice-president of global marketing with InetSoft. "The first is this access to the disparate data sources. The second is a middle layer that provides data mashup and cache, and interfaces with a product that we call a Data Worksheet, which is a spreadsheet-like worksheet that’s easy to use. The final piece is this rich presentation front-end, which includes tools like visual exploration, scorecarding and dashboarding, and OLAP."

iSuite’s connectivity is primarily delivered by means of JDBC, officials say. "We can connect to just about any data source. When we connect to databases, if it’s a relational database, we typically go through JDBC; if we’re pulling from XML or Web services, we use XQuery or SOAP," indicates Byron Igoe, chief BI technologist with InetSoft. To access applications or data sources that won’t accept JDBC connections, he says, developers can use the Java Object Data Source (JODS) to code connectivity on their own. "We use a ‘catch-all,’ if you will: the Java Object Data Source, so you basically build a little helper class, and that will help us get into any data source," Igoe explains.

Using InetSoft’s "Data Block" technology, iSuite can build and persist a metadata "view" of heterogeneous data. "With the exception of caching, we’re always pulling [data] in real time. Our focus is always on the operational side. The blocks themselves can be thought of as the logic to pull the data, a metadata layer if you will, and the metadata itself is stored [in iSuite]," Igoe explains.

The Data Block concept carries over into iSuite’s visual design environment, which lets users visually explore data block assemblies at the "atomic" level, via the manipulation of discrete Data Blocks. In this respect, Stern says, users can also drag and drop Data Blocks to create imaginative mash-ups of data sources. Organizations can use iSuite to expose either static or advanced analysis or report generation capabilities to users, depending on the requirements (and abilities) of the users themselves. For example, Stern says, organizations can pre-build relatively static dashboard or scorecard views for users who don’t need to interact with data, or who otherwise won’t be manipulating data or drilling down data to analyze it. For power users, on the other hand, iSuite can facilitate a range of sophisticated scenarios.

"I can do filtering, I can build expressions, basically derive formulas off of the data that’s currently there, even some things that you can’t do with standard SQL, like a rotate, which basically does a transposition, turning the rows into columns, also converting [the data] into an embedded table. This will take a snapshot of the current table and then allow me to embed it; it’s very useful for a ‘what-if’ analysis," Stern says. iSuite’s connectivity capabilities also let power users, analysts, or even data architects perform on-the-fly joins. "Really it gives you all of the power of SQL and then some, because I have additional operations as well as the ability to mash-up multiple operations into a single data set."

This latter capability, coupled with iSuite’s canned connectivity features, helps make it a good candidate for a data warehouse modeling tool, or as a "precursor" to a full-fledged data warehouse. "One use case is as a precursor to a data warehouse because if you’re thinking about adding a new data source, you can expose it as a mash-up before going through the cycle of setting up the ETL to make it part of your data warehouse," he explains. In other cases, Igoe says, organizations might not want to bring some data into the DW: "For these smaller data sets that you may not want to provide as part of your [data warehouse] data sets, you can still connect them up along with your DW. Even though they’re not part of the data warehouse, your users can still access them."