In a recent Forrester report “Enterprise Business Intelligence Platforms, Q3 2008”, arrive the following conclusion
IBM Cognos, Oracle, SAP Business Objects, and SAS Lead The Market
In Forrester’s 151-criteria evaluation of enterprise business intelligence (BI) platform vendors, we found that IBM Cognos and SAP Business Objects maintain their leadership positions, while Oracle and SAS Institute move into leadership positions in enterprise BI thanks to the richness of
their functionality, ability to scale, and the completeness of their corporate and product vision and strategy. Actuate, Information Builders, Microsoft, MicroStrategy, SAP, and a new entrant, TIBCO Spotfire, came out as Strong Performers following very closely on the heels of the Leaders, offering very respectable alternatives and a multitude of choices for information and knowledge management (I&KM) professionals. New entrants to this Forrester Wave™ evaluation of enterprise BI platforms (though not new to the market) are Panorama Software and QlikTech, who, while lacking the breadth of features to qualify them as single, large-enterprise BI solutions, are reputable Contenders. In some very specific BI use cases, they even outperform the Leaders.
The report highlights the changing face of BI and points the importance of Dashboards as an integral piece of Business Intelligence
It goes on the explain the different components of BI
BI requires many different components — sometimes more than 40 — to deliver large enterprisegrade,scalable, robust, secure, and function-rich BI environments . While this Forrester Wave evaluation places heavy emphasis on the reporting, analytics, and information delivery layers of the BI architectural stack, it also addresses dependencies on all the other components like data discovery, integration, and data quality management. Reporting is just the tip of the iceberg.
The report classifies the core BI component into the following 8 main sections by functionalities.
Production/operational reporting for pixel-perfect mass report distribution. No matter how much BI self-service end users request, good old-fashioned report development tools — mainly used by professional programmers — remain at the heart of a BI product line. While these tools
may also be used to analyze data and produce visual dashboards, they are primarily used for mass distribution of very sophisticated reports like customer statements. Requirements for these products often include pixel-perfect positioning of data and graphics, a scripting language equal in power to a full programming language, and the ability to handle complex headers, footers, nested subtotals, and multiple report bands on a single page
Ad hoc query tools provide a quick answer to a business question. When report formatting or distribution is not a requirement, and an I&KM professional just needs a quick answer to a business question like, “How many units of a product were sold yesterday across all stores and outlets?” or, “What were my total sales in 2007 in North America?” simple ad hoc query tools
with an intuitive point-and-click user interface (UI) are the way to go
OLAP tools, when business questions are more about “whys” than “whats”. While reporting and ad hoc query tools are typically used to answer the questions lik e “What happened?” and “When and where did it happen?”, online analytical processing (OLAP) tools are used to answer the questions like “Why did it happen?” and also to perform “What if?” analysis. Otherwise known and “slicing and dicing” analysis (essentially a spreadsheet pivot table on steroids),
OLAP tools allow a power user to see any facts (numerical, typically additive numbers, like transaction amounts and account balances) almost instantaneously regrouped, re-aggregated and resorted by any dimension (descriptive elements like time, region, organizational unit, or product line).
Dashboards as an interactive, visual UI — not a reporting or analytical tool by itself.
Dashboards should be used as a UI to operational or analytical information. Designed to deliver historical, current, and predictive information typically represented by key performance indicators (KPIs), dashboards use visual cues to focus user attention on important conditions, trends, and exceptions.2 The term “dashboard” is often used synonymously with “scorecard,” but
Forrester defines a scorecard as just one type of a dashboard that links KPIs to goals, objectives, and strategies. Many scorecards follow a certain methodology, such as Balanced Scorecard, Six
Sigma, Capability Maturity Models, and others.3 Other dashboard varieties include business activity monitoring (BAM) dashboards and visualizations of data/text mining operations
BAM to report on real-time data and process information streams. While a dashboard can be used as a graphical UI (GUI) component, business activity monitoring (BAM) also captures
data and process events (e.g., number of credit applications processed today and number still pending in a queue), correlates and aggregates them into business metrics (e.g., ratios of
processed, approved, and rejected applications per hour), and displays the real-time status of the metrics and trailing patterns
Predictive modeling answers questions about what’s likely to happen next. Using various statistical models, these tools attempt to predict the likelihood of attaining certain metrics in the future, given various possible existing and future conditions. One typical predictive modeling class is called market basket analysis, which tries to predict the likelihood of a customer buying a certain product if and when he or she bought another product at a certain store at a certain season, date, and time, given certain economic conditions such as interest rates and price of gas.
BI workspaces enable true end user self-service. While most BI environments attempt to address end user self-service requirements, they still impose many restrictions, such as fixed
data models, an inability to add new dimensions on the fly, and sometimes restricted access to production data. Forrester defines a BI workspace as a data exploration environment where a power user can analyze production, clean data with near complete freedom to modify data models, enrich data sets, and run the analysis whenever necessary, without much dependency
on IT and production environment restrictions. Some examples of such workspaces are desktop based multidimensional OLAP (MOLAP) cubes, in-memory data models, or BI software-as-aservice
Guided BI search tools support free form ad hoc queries and analysis. While reporting, ad-hoc queries, and OLAP tools work best when one knows the exact business question, they fall
short when a user is looking for something that he or she is not quite sure of. A salesperson getting ready for an important client meeting may not know all of the information required to
prepare for the meeting and may not be able to effectively construct the appropriate queries to pull the information she might need. What works much better is enabling this salesperson to
simply enter a few keywords to find relevant customer dimensions in the database, then using a graphical interface to drill into the information she wants from a list of possibilities. This effectively solves one of the oldest dilemmas in BI: having to know exactly which questions to ask to get a meaningful answer
So is this report meant only for the “Rich Guys?” Ofcourse this report is designed to help Big corporations make better decisions when they are ready to make a purchase or evaluate BI tools.
This report certainly does not cater to the small and medium business audience. Most often SMBs are in the lookout for Ad-hoc reporting or just plain Dashboards. This report is definitely a good read as it alteast educates the core components of BI.