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June 19, 2012

Location Intelligence Completes BI Puzzle

Datanami Staff

With more data than ever coming from mobile devices, expanding networks of sensors, GIS systems and other location-aware tools, location intelligence is becoming an invaluable part of business intelligence. This is due, in part, to the ease with which this data can be melded with existing databases as well as the native integration of such tools within existing BI platforms.

The field of location intelligence has undergone a significant amount of “democratization” over the last couple of decades, in part due to the open APIs and availability of GIS and satellite data. Prior to the era of openly accessible (and easily usable) geographic data, companies like ESRI dominated the burgeoning GIS market—mostly because of the complexity of that data and the expertise needed to make use of it.

While ESRI and others who pioneered the space are still around, they’ve had to adapt to a rapidly changing ecosystem, which challenges their gatekeeper status on the GIS front and forces a joining of forces with the once-separate realm of business analytics platforms.

Galigeo, which was founded in 2001 after spinning off from France Telecom, was one of the early companies to explore the possibilities and technologies behind integrating businessintelligence and location intelligence.

The company is one of several that blend GIS and other location information with existing data inside enterprise systems. Galigeo has found a sizable market for their services, especially in the public sector, with customers like the State of Illinois, the European Commission, the State of Geneva, and several other European and American government entities.

Galigeo’s implementations utilize a wide of range of GIS (geo-spatial) data. The goal is to “spatially enable” many multiple sets of geo-spatial data easily from multiple data stores from our solution. According to Timothy Morrissey, the company’s senior software consultant, this reduces the amount of ETL effort a GIS team must deal with.

The company claims that is able to extend “the Geo-Spatial value proposition” by integrating a vast of amount business process and performance data that already exists inside the organization (BI databases, analytics cubes, OLTP transactional data, finance and revenue, and the ubiquitous data warehouse).  “This is where the company is completely unique,” says Morrisey, who states, “the power of our solution comes from the ability to seamless integrate a wide range of geo-spatial data with an equally wide range of business intelligence data.”

For example, in a retail sector implementation this can be as simple as representing store locations as not only “points on a map”, but intelligently representing store revenue or performance data (customer visits, loyalty rates, revenue, etc.). This integrated visualization allows for the more informative representation of patterns or highlighting outcomes in a manner that allows more rapid assimilation of the information.

To highlight this, the company points to a use case of how a retail outlet can take geo-point data to a store location, then marry that data with BI data showing store performance.

While this is more of a “standard” use case, Morrissey says there are some particularly unique uses of the company’s platform. This is contained in what they call “inside GIS.” He highlights this concept with an example of a shipyard that houses the construction elements for large cruise ships.

When it comes to unique uses of business intelligence that taps into GIS an location-driven platforms, Galigeo says there are numerous examples. One that they point to as particularly stand-out involves STX Europe, which builds very complex vessels requiring the assembly of tens of thousands of parts themselves aggregated in building units.

Galigeo’s senior software consultant, Timothy Morrissey says that typically, the design and construction of a vessel can take from 3 to 36 months and requires the chronological tracking of each unit of construction for quality compliance across the entire build of the vessel. It also involves other complexities, including the involvement of quality inspectors who constantly review the construction process and then report their findings through an SAP based system. This information guides engineers and shipyard workers to plan and execute corrective actions. However, he says, the challenge is to have a spatial view of the build activities within a unit and an understanding of the interrelation between units. 


Said another way, there is a need to match R&D Micro Station designed shapes (Geo data) with SAP quality indicators (BI data). Without a central map-like view, communication between management, quality inspectors and engineers breaks down hindering construction progress and adding costs.

One of the workarounds was to extract data from each system to manually create a daily report in Excel. Morrissey says this is a repetitive time consuming process whose results are not easily shared among different teams involved in the vessel construction effort.

As Morrissey told us, “Galigeo, implemented WEBIGEO to automate the daily generation of the ship’s quality map-like view. Inside a cross section map, each building unit is attributed a color-coded compliance rate. The map mirrors the vessel’s evolving silhouette. The heat-map based reports help focus quality controls actions and naturally increase managers’ fault correction reactivity. Management, R&D teams, engineering and quality controllers are more fully informed as to current day status of quality performance and are able to better align their remediation efforts to correct quality issues in any building unit in a more timely manner.  This speeds the overall building of the vessel and helps the contractor achieve delivery timeframes.”

As further follow-up we put a few tough questions to Morrissey about the company’s business, competitive advantages in a market already laden with similar pre-integrated offerings, and its approach to growing data complexity.

How does your company not only help users with their “big data” analytics needs but also manage the flood of data needed for a GIS-based business or is all the data handled remotely by outside parties (ESRI)?

As part of our solution delivery process, we work with our customers to analyze their existing data resources to identify how location can be utilized as part of their strategic analytics initiatives. A vast amount of existing data in the company’s BI systems, OLTP systems or data warehouse has a location component to it. Interrogating existing data components and business processes to uncover the potential of a Location Analytics implementation is a key value-added process for transforming data into useful information. Along with re-examining existing data assets, we offer expertise in what spatial datasets are best suited for specific industry verticals. This process, of working with existing data, identifying industry specific geo-spatial assets, and working with data provider partners, allows us to develop a comprehensive Location Analytics solution.

With nearly all of the major business analytics platforms integrating their own location analytics and intelligence pieces, how will maintain your edge—in other words, what makes you different?

One of our competitive advantages is the overall design of our product and our solution.  We have off the shelf connectors (think API’s) designed to more easily integrate to leading BI providers.  This means we can “plug and play” into almost any Enterprise Business Systems Architecture environment.  If your data has been consolidated into a warehouse we can connect.  If you have a BI, CRM and OLTP systems we can connect. If you have multiple BI platforms (i.e. Cognos, Business Objects and Oracle) we can connect.  Simply, we offer our customers a comprehensive technical platform for implementing a Location Analytics solution across a multitude of enterprise information systems.  

As well we also provide the knowledge and expertise on how location can be an essential informational decision making asset across a number of industry sectors. Most large organizations employ multiple disparate data systems across the enterprise (CRM, SCM, ERP, BI, etc).  Our customers benefit from our real-world experience and understanding of how to integrate these data rich platforms with our solution.  In this approach we deliver a Location Analytics implementation, in which data from these systems is both spatially enabled and also spatially informed through decision making workflows.

This combination of technology and expertise allows us to provide a comprehensive Location Analytics solution to our clients so that they can quickly synthesize key business information in a manner that allows them to make decisions as to the next “best action” to improve their business.            

So far users can access data from SAP BusinessObjects, IBM Cognos and databases including SQL Server, SQL, Teradata and Oracle. What are you plans for the future of allowing greater access and more important, how does your business change in the wake of NoSQL and other frameworks for large-scale data management (i.e., Hadoop, etc).

As the shear magnitude of data, and specifically location data continues to rapidly expand with sensors and smart phones the role of distributed data storage and management systems will become increasingly important for curating this volume of data into useful information. We already have a universal connector for “ODBC” integration that when configured enables access to legacy and orphan databases.  As well, we have developed integration credentials with WebFocus. 

The flexibility in our solution architecture allows us to be nimble in response to changes in the enterprise computing landscape. For example, as frameworks like Hadoop continue to gain adopters and deployment into the enterprise we will continue to evolve our platform to best meet the needs of our customers.  The evidence of this is our product roadmap and product strategy. We are currently focused on building the connectors to MicroStrategy and Netezza and will evaluate other emerging frameworks or solutions.

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