This article discusses the requirements for selecting a business intelligence platform, contrasted with the shortcomings of older BI solutions.
When business intelligence software was in its infancy, most approaches were based on simple arithmetic calculations (summation, division, ranking, etc.) focused on the analysis of historical (last year, last quarter, last month) data. For those purposes, data warehouses were great at aggregating data in batches from different operational systems based on predetermined data models at certain intervals, but they suffered from latency; changes required retuning queries or time-consuming re-architecting of data models; most data warehouses weren't scalable enough to handle transaction-level data granularity.
Another type of software that was used in the broader context of business analytics included rules engines. Rules engines were, in most cases, more flexible than data warehouses in providing support for transaction monitoring, but they required prebuilt rules. Case management systems were strong at managing workflows, but usually just took alerts from individual operational systems; their siloed data capture presented a deficiency in accuracy and insight.
Realizing those shortcoming's, nowadays a complete BI architecture must take into account the different potential user constituents and their varying needs. For example, executives may require exception-based dashboards, while analysts require full-featured OLAP and query building tools; line-of-business staff need operational reports, while external stakeholders, such as suppliers, customers, and partners, may require other related BI functionality. Therefore, there is a need to combine traditional data warehousing tools with operational BI components.
Organizations should consider embedding analytics within all business processes supported by operational applications. In other words, whenever a decision needs to be made in a business process, an opportunity exists to inject intelligence into that process. This can be done through better and faster data capture, more advanced analytics, and work flowœbased information delivery to decision makers or other applications. This type of intelligent process automation automates repeatable, operational decisions in response to events where analytics drive the business process workflow.
Indeed, since many types of decisions are recurring or repeatable, decision-making processes exist that are amenable to automation. For example, organizations should consider automating processes that detect suspicious transactions, set prices, recommend products or services, extend credit, or monitor product quality.
The requirements of intelligent process automation above and beyond traditional BI include:
Another benefit of business intelligence software is that it enables greater consistency in the way decisions are made. This is important not only for competitive reasons but also, increasingly, for compliance reasons – companies must demonstrate that decisions were not arbitrary, but followed established procedures.
InetSoft Technology Corp., founded in 1996 and headquartered in Piscataway, NJ, is a software development and service company providing Java-based enterprise reporting and BI solutions. InetSoft software, based on process-aligned intelligence designs that center on the company's patent-pending Data Block technology, provides a secure, scalable, and collaborative operational BI platform for real-time information flow.
The software's full-featured presentation front end enables an intelligence flow of information that aligns with an organization's ongoing business process. Data Blocks assembled for one process step can serve as the building block for the next step's intelligence needs by adding to the previous level of intelligence. InetSoft's reporting, analytics, and monitoring tools can aggregate, compare, and visualize shared Data Blocks for a wide spectrum of business users.
InetSoft's process-aligned software design provides business line managers with real-time data to make decisions that impact the bottom line. Leveraging this intelligence in a collaborative environment across the enterprise provides business managers with the ability to make operational decisions that positively impact related business processes.
InetSoft's Data Block technology also offers inherent On-Demand Federated Data capabilities that allow data integration to cross-organizational boundaries wherever business processes require it. Business users can combine, transform, and filter structured and unstructured data from a wide breadth of formats and sources. Leveraging this technology, pre-purposed BI data sources, such as data warehouses, operational data stores, and OLAP data sources, can be combined with transactional data. InetSoft's On-Demand Federated Data enables business managers to make quicker, better-informed business decisions and process enhancements without IT resource support.
InetSoft Data Block technology combines a secure and scalable Data Federation engine with an intuitive data-worksheet user interface, so business users can access, assemble, analyze, and collaborate on vital information in real time.
InetSoft software, built on a 100% Java Web-based platform, offers a versatile data layer that facilitates business process collaboration on both dynamic and static data. Its presentation layer enables both professionally designed production reports and user-created ad-hoc reports. Advanced BI functions include OLAP analysis and interactive dashboards integrated with alert notification capabilities. The industry-standard J2EE application server is optimized to ensure a secure, high-performance, and scalable platform for global enterprise needs.
To support its product sales, InetSoft has also established a separate business unit, Professional Consulting Services. The company's consulting staff assists users of its business intelligence solutions with custom training and report design, data access, data modeling, data management, project management, and implementation needs.