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bi service pune Business intelligence (BI) software is a collection of decision support technologies for the enterprise aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions.
The past two decades have seen explosive growth, both in the number of products and services offered and in the adoption of these technologies by industry. This growth has been fueled by the declining cost of acquiring and storing very large amounts of data arising from sources such as customer transactions in banking, retail as well as in e-businesses, RFID tags for inventory tracking, email, query logs for Web sites, blogs, and product reviews.

Enterprises today collect data at a finer granularity, which is therefore of much larger volume. Businesses are leveraging their data asset aggressively by deploying and experimenting with more sophisticated data analysis techniques to drive business decisions and deliver new functionality such as personalized offers and services to customers. Today, it is difficult to find a successful enterprise that has not leveraged BI technology for its business. For example, BI technology is used in manufacturing for order shipment and customer support, in retail for user profiling to target grocery coupons during checkout, in financial services for claims analysis and fraud detection, in transportation for fleet management, in telecommunications for identifying reasons for customer churn, in utilities for power usage analysis, and health care for outcomes analysis.

Data warehouse servers are complemented by a set of mid-tier servers that provide specialized functionality for different BI scenarios. Online analytic processing (OLAP) servers efficiently expose the multidimensional view of data to applications or users and enable the common BI operations such as filtering, aggregation, drill-down and pivoting. In addition to traditional OLAP servers, newer "in-memory BI" engines are appearing that exploit today's large main memory sizes to dramatically improve performance of multidimensional queries.


Reporting servers enable definition, efficient execution and rendering of reports—for example, report total sales by region for this year and compare with sales from last year. The increasing availability and importance of text data such as product reviews, email, and call center transcripts for BI brings new challenges. Enterprise search engines support the keyword search paradigm over text and structured data in the warehouse (for example, find email messages, documents, history of purchases and support calls related to a particular customer), and have become a valuable tool for BI over the past decade.


Data mining engines enable in-depth analysis of data that goes well beyond what is offered by OLAP or reporting servers, and provides the ability to build predictive models to help answer questions such as: which existing customers are likely to respond to my upcoming catalog mailing campaign? Text analytic engines can analyze large amounts of text data (for example, survey responses or comments from customers) and extract valuable information that would otherwise require significant manual effort, for example, which products are mentioned in the survey responses and the topics that are frequently discussed in connection with those products.

There are several popular front-end applications through which users perform BI tasks: spreadsheets, enterprise portals for searching, performance management applications that enable decision makers to track key performance indicators of the business using visual dashboards, tools that allow users to pose ad hoc queries, viewers for data mining models, and so on. Rapid, ad hoc visualizationof data can enable dynamic exploration of patterns, outliers and help uncover relevant facts for BI.