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Although the business intelligence (BI) market is growing again at a lightning-fast pace, it has so far failed to deliver a great experience to the designers and consumers of modern analytics. Yesterday’s BI solutions are being displaced by “agile” providers that move beyond basic reporting, dashboards, and ad hoc analysis. Yesterday’s BI stack (e.g., the layering of OLAP engines, ETL technologies, and data warehouse solutions) is completely incapable of solving modern analytical challenges.Today’s BI and analytical apps are built and consumed by the line-of-business owners. These analytic creators and consumers are supported by five key trends that are disrupting the traditional BI stack: big data, cloud computing, location intelligence, the social enterprise, and mobility. Together, these macro-trends are shaping the next generation of BI and analytics solutions. Traditional business intelligence (BI) and analytic models are being disrupted as the balance of power shifts from IT to the business, according to Gartner, Inc. The rise of data discovery, access to multistructured data, data preparation tools and smart capabilities will further democratize access to analytics and stress the need for governance. Gartner predicts that by 2017, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis


With recent advancements in computing technology, operational intelligence has finally become a reality. While business intelligence provides insights for static datasets, usually identifying long-term trends based on historical data, operational intelligence targets short-lived business opportunities, offering timely, actionable insights. Operational intelligence tracks the behavior of live systems, integrating streaming data with customer preferences and historical information to create a comprehensive view and generate immediate feedback.


Recent advancements in in-memory computing technology have paved the way for operational intelligence. In-memory computing eliminates the bottlenecks inherent in the techniques used for business intelligence. For example, it avoids the overheads of disk-based data storage and batch scheduling, enabling the immediate, efficient tracking and analysis of live data. Unlike pure streaming and event-processing systems, operational intelligence uses in-memory computing to maintain a comprehensive picture of customer activity, leading to a deeper understanding of and customer needs. Moreover, operational intelligence incorporates techniques that ensure uninterrupted processing .With operational intelligence, companies now are able to analyze the fast-changing data they manage within operational systems, enriching it with historical information and analyzing it for patterns and trends that require immediate action. While business intelligence provide strategic guidance from the data warehouse


Business intelligence has gone through multiple iterations in the past few decades. While BI’s evolution has addressed some of the technology and process shortcomings of the earlier management information systems, BI teams still face challenges. Enterprises are transforming only 40% of their structured data and 31% of their unstructured data into information and insights. In addition, 63% of organizations still use spreadsheet-based applications for more than half of their decisions. Many earlier and current enterprise BI deployments:

  • Have hit the limits of scalability.
  • Struggle to address rapid changes in customer and regulatory requirements.
  • Fail to break through waterfall’s design limitations.
  • Suffer from mismatched business and technology priorities and languages.


Capabilities to collaborate electronically and carry out complex activities while mobile have matured to the point where they are influencing business intelligence (BI) and information management in significant ways. Our research shows that 70 percent of organizations either have deployed some type of mobile business intelligence or hope to deploy it in the near future. These developments raise questions for enterprises and software vendors alike. What role should collaborative and mobile technologies play in BI applications?  The intersection of mobile technologies and social media with business intelligence creates new possibilities. Mobile technologies have already exerted significant influence over BI processes and forced most BI software vendors to offer mobile capabilities.

BI Solutions Must Address The Information Management Matrix

A confluence of changing business requirements and on-going vendor consolidation leads many organizations to rethink their business intelligence (BI) strategies

By: Annie steffi Sydney.,ME 2nd year


Loyola institute of technology and science,thovalai,kanyakumari dist,tamilnadu

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