With the release of SAP BusinessObjects Enterprise 4.0 (BOE 4.0), Explorer 4.0 and SAP HANA, there is new way to achieve unbelievable performance when exploring large data sets. This article will provide an overview of the tools, the components and the value the solution offers an organization.

When Explorer was first released several years ago it was actually named Polestar. For those that have browsed through the backend of the SAP BOE 4.0 server, you have likely seen files and folders with the Polestar name. It was a new concept tool that allowed users to intuitively filter, aggregate, and visualize data in conjunction with simple metrics. SAP explains the solution as:

“SAP BusinessObjects Explorer™ software brings together the simplicity and speed of Internet search with the trust and analytical power of BI to provide immediate answers to business questions.”

Now that we have heard the marketing spiel, I would like to walk you through the ins and outs of Explorer. When you first log on to Explorer and open an Information Space, on the top left side you will see a listing of the measures. (Click to see Image) Measures are the values that you sum, min and max within the configured data set. You can select one or more measures as well as create simple custom calculations. The overall data set is referred to as the Information Space. It is traditionally updated and indexed on a scheduled basis by an administrator or developer. Hold this thought though because this is where HANA adds real value.

Listed across the top of the canvas are the facets. Facets are a fancy name for dimensional data within the information space. Each facet contains the top or bottom values accompanied with a ranked aggregate (based on the highlighted measure on the left side). (Click to see Image) This area allows you to quickly identify your top or bottom values within each facet. You will also find that clicking on a facet’s value adds the selected value as a filter to the overall information space.

At the bottom of the canvas lie the visual chart components and ranking tables. At the top of the chart area you can change the measure and “Group By” facet. To the right of the charts you will see the ranking table. There are several charts to choose from that will allow Explorer to quickly visualize the selected dimension and measures. You can also change the sort options, Top N ranking value and enable/disable the “Other values” option. The “Other Values” option is provided to compare each Top N values to the total of all other values. There are charts to help users compare one or more measures and there are also trend analytics to help users quickly see the directions their measures are moving.

SAP Explorer is also mobile enabled. There is both an iPhone and an iPad application that can connect to your published information spaces with little setup required. If you are looking to implement an easy mobile solution, Explorer might be your best option. In Feature Pack 3, which will be released very soon, SAP has added the capability for users to create their own layouts similar to Dashboards. These new components are called Exploration Views and they will help to add even more power to Explorer.

If you want to see more examples of Explorer you can Google “youtube SAP Explorer”

Now let’s dig a little deeper into the backend of Explorer. At its heart, Explorer is an add-on to the BOE 4.0 platform. It consists of four backend java based services that can be managed in the CMC. It also consists of a Java Web Application that is embedded within Tomcat or other supported Java Web Servers. When you create an Information Space natively in BOE 4.0 you have to select an IDT Universe and create a query containing dimensions, measures and conditions (filters). Once the query is created, you then schedule it for indexing. When the indexing processes start, the backend services work together to create an information space. That information space is then cached on the disk drive where the Explorer services are installed. When you access the standard Information Space the data is requested directly from this disk index or cache. When dealing with highly aggregated data, this cache provides superior performance compared to reissuing a SQL query to a database multiple times. This is especially important if the database is managing millions of detailed records. However, this disk-based cache is limited in its ability to manage large or “high granularity” data sets that exist even after being aggregated or filtered. In my experience, the performance breakdown occurs when more than 3 to 5 million rows of data are stored in the traditional information space.

SAP’s first attempt at addressing this problem came in the form of the SAP BW Accelerated (BWA) combined with SAP Explorer Accelerated. This solution allowed Explorer to directly access the highly indexed infocubes in BWA to increase its performance. While this solution provided better performance and scalability, it still lacked in its ability to scale to really “big data” levels. This solution also only provided benefits to companies that incorporated BWA into their landscape.  If you were a legacy BOBJ customer seeking Explorer performance gains, BWA was not your solution. There is, however, a bright side with the addition of HANA.

With the release of SAP HANA, all organizations now have options to accelerate their SAP Explorer environment and also explore data sets that consist of hundreds of millions of records. To make this solution work, Explorer 4.0 can now bypass its local Information Space cache and connect directly to the in-memory columnar data and calculation engines found within SAP HANA. When configured correctly on BOE 4.0, Explorer will recognize any Analytic or Calculation View created on SAP HANA via a relational connection stored in the BOE repository. (Click to see Image) In short, this solution does not need a universe, a query or disk cache to power the information space.

At a minimum, organizations will need the following software to enable this solution:

• An instance of SAP HANA standalone 1.0 SP2 V20
• SAP BusinessObjects Enterprise 4.0 or SAP BusinessObjects EDGE 4.0 (SP2 FP11)
• SAP BusinessObjects Explorer 4.0  (SP2 FP11)
• LT replication server or Data Services 4.0 SP2 to load data into a HANA instance

When you combine the power of SAP HANA with Explorer, you will find that the traditional limitations to multidimensional analysis (MDA) are no longer an issue. Native Explorer was not unique in its inability to manage “big data” sets while providing deep analysis. In general, most MDA OLAP cubes or MDA ROLAP solutions were limited by the old model of disk-based storage. With the emergence of servers supporting terabytes of RAM and multiple CPU cores, it was time to move into the next generation of data storage and access. HANA combined with SAP BusinessObjects is a perfect solution to move data analysis into the next generation.

SAP Explorer is not the only SAP solution that benefits from HANA but there are specific reasons that I believe Explorer based on HANA offers great value to an organization.  There are three main reasons I see this solution adding value to organizations eager to empower users to analyze data.

The first reason is based on how easy and intuitive the tool is to learn. Most ad-hoc analytic tools can be overwhelming to non-technical business users because they contain too many bells and whistles that distract them from analyzing the data. In addition, most dashboarding tools are too complex for users to create meaningful and dynamic work spaces. In my opinion, Explorer is a hybrid of ad-hoc reporting and dashboard design. With Explorer, users will be able to develop self service analytics reducing their reliance on technical IT resources. This will be even more evident with the release of Exploration Views in Feature Pack 3.

The second reason I see this as a great solution is based on the abilities of HANA. With HANA powering Explorer, detailed data can be explored, compared and analyzed over multiple years. The volumes of data that HANA can manage are quite remarkable compared to native Explorer’s abilities. In a recent POC I conducted, we were able to explore a HANA-based information space that contained over 250 million rows at the lowest level of granularity. This allowed the users to recognize trends, compare KPIs, and drill into details of data that where previously unobtainable. Having access to all the attributes and details of a data set can be quite valuable to users that find their perfect question only after looking through several answers. When data is filtered or aggregated to increase analytic tool performance, details are often removed from the data to help make the tool more usable. In some cases these details might have provided valuable insight. With HANA there is no reason to aggregate or filter the data.

The final reason that I see great value in this solution is based on how easy it is to deliver the solution to mobile devices. Users can access detailed data from anywhere or at any time without the limitations of filtered or partial data sets. Most of the current mobile solutions available are limited to smaller data sets for performance reasons or they are limited by the need for IT developers to create the analytics. Mobile Explorer is both easy to deploy and easy to use.

Hopefully this article has given you further insight into this new solution. Based on my first hand experience, this solution has more potential than many other solutions currently available by any vendor. It is also worth noting that Explorer is not the only tool or application that can benefit from SAP HANA. There are today, and will continue to be in the future, a number of solutions that are enhanced by the existence of SAP HANA.