Is "business intelligence" a buzzword that has no real meaning to software developers, or does the term carry some implied meaning in terms of what the software does or how the software does it (in a general sense)? It appears to be a real business term, but does it mean anything in particular to software that performs business intelligence tasks?
Business intelligence (BI) tools are types of application software that collect and process large amounts of unstructured data from internal and external systems, including books, journals, documents, health records, images, files, email, video, and other business sources.
It's increasingly important for businesses to have a clear view of all their data to stay competitive, which is where business intelligence (BI) tools come in. After all, nearly 50% of all businesses already use BI tools, and projections show continued growth in coming years.
The business intelligence end-user can be defined as a decision-maker (of any level within the company), who does not necessarily possess IT skills and who uses business data and information from the BI solution to guide his actions.
Business intelligence systems combine data gathering, data storage, and knowledge management with data analysis to evaluate and transform complex data into meaningful, actionable information, which can be used to support more effective strategic, tactical, and operational insights and decision-making.
BI != Reporting. BI platforms enable users to build applications that help organizations learn and understand their business. Gartner defines a BI platform as a software platform that delivers the following 12 capabilities:
Integration
- BI infrastructure — All tools in the platform should use the same security, metadata, administration, portal integration, object model and query engine, and should share the same look and feel.
- Metadata management — This is arguably the most important of the 12 capabilities. Not only should all tools leverage the same metadata, but the offering should provide a robust way to search, capture, store, reuse and publish metadata objects such as dimensions, hierarchies, measures, performance metrics and report layout objects.
- Development — The BI platform should provide a set of programmatic development tools — coupled with a software developer's kit for creating BI applications — that can be integrated into a business process, and/or embedded in another application. The BI platform should also enable developers to build BI applications without coding by using wizard-like components for a graphical assembly process. The development environment should also support Web services in performing common tasks such as scheduling, delivering, administering and managing.
- Workflow and collaboration — This capability enables BI users to share and discuss information via public folders and discussion threads. In addition, the BI application can assign and track events or tasks allotted to specific users, based on pre-defined business rules. Often, this capability is delivered by integrating with a separate portal or workflow tool.
Information Delivery
- Reporting — Reporting provides the ability to create formatted and interactive reports with highly scalable distribution and scheduling capabilities. In addition, BI platform vendors should handle a wide array of reporting styles (for example, financial, operational and performance dashboards).
- Dashboards — This subset of reporting includes the ability to publish formal, Web-based reports with intuitive displays of information, including dials, gauges and traffic lights. These displays indicate the state of the performance metric, compared with a goal or target value. Increasingly, dashboards are used to disseminate real-time data from operational applications.
- Ad hoc query — This capability, also known as self-service reporting, enables users to ask their own questions of the data, without relying on IT to create a report. In particular, the tools must have a robust semantic layer to allow users to navigate available data sources. In addition, these tools should offer query governance and auditing capabilities to ensure that queries perform well.
- Microsoft Office integration — In some cases, BI platforms are used as a middle tier to manage, secure and execute BI tasks, but Microsoft Office (particularly Excel) acts as the BI client. In these cases, it is vital that the BI vendor provides integration with Microsoft Office, including support for document formats, formulas, data "refresh" and pivot tables. Advanced integration includes cell locking and write-back.
Analysis
- OLAP — This enables end users to analyze data with extremely fast query and calculation performance, enabling a style of analysis known as "slicing and dicing." This capability could span a variety of storage architectures such as relational, multidimensional and in-memory.
- Advanced visualization — This provides the ability to display numerous aspects of the data more efficiently by using interactive pictures and charts, instead of rows and columns. Over time, advanced visualization will go beyond just slicing and dicing data to include more process-driven BI projects, allowing all stakeholders to better understand the workflow through a visual representation.
- Predictive modeling and data mining — This capability enables organizations to classify categorical variables and estimate continuous variables using advanced mathematical techniques.
- Scorecards — These take the metrics displayed in a dashboard a step further by applying them to a strategy map that aligns key performance indicators to a strategic objective. Scorecard metrics should be linked to related reports and information in order to do further analysis. A scorecard implies the use of a performance management methodology such as Six Sigma or a balanced scorecard framework.
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