Business Intelligence Basics

CITIBANK

Shweta Mangrole

shweta.mangrole@tcs.com

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Table of Content

1. What is Business Intelligence? .................................................................................................................................. 5

2. BI Concepts. .............................................................................................................................................................. 5

3. BI Components .......................................................................................................................................................... 6

4. Conclusion ................................................................................................................................................................. 8

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Shweta Mangrole hold a Btech in Instrumentation & Control and currently working as a System Engineer . She has 3 years of experience and currently allocated to CITIBANK account in Mumbai . She got trained in BIPM and working on Process Quality Assurance.

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1. What is Business Intelligence? Business Intelligence, Decision Support Systems, Informational Environments are some terms to name the efforts to convert all transactional data generated by daily activities of some organization into valuable and timely information to make accurate decisions, to measure the performance of this organization in known indicators inside this organization or to benchmark this company against competitors with this indicators.Everyone is involved.This definition is very high-level one. The experience through many Business Intelligence projects indicates that the process involves every single part of the company to be analysed, it means: data producers (every involved data-cruncher system and user), data analysers, information consumers, decision-influencers, decision-makers and IT multi-disciplined teams to achieve the ultimate goal: give to all the appropriate tools to make the most successful decisions.

2. BI Concepts.

There are lot of concepts and terms that it is necessary to know and handle when a team is working with Business Intelligence issues. In order to really understand all these concepts and its relationships, it is necessary to group these terms by functions inside the whole Business Intelligence Design and Implementation.

Instead of established concepts, every organization establishes its own interpretations for every term, so this traning material contains the most utilized interpretation for every term or concept.

From the functional point of view, we have these groups of components:

Transactional or Operational Systems – Source Data Systems: The main source for business intelligence data to be analysed is all data captured, processed and reported by all core transactional systems for the company or organization.

Data Transfers Processes – Data Interfaces – ETL Processes: All necessary data must be processed from source data systems to a specialized repositories or to show to final users. These data interfaces are called ETL (Extract, Transform and Load) processes.

Data Repositories: Depending on the size and the reach of this repository, it could be named data warehouse: when the stored data is about all organization or the most of this organization; or could be named datamart when the stored data is about isolated departments or organizational units.

Final Users Tools: For obtaining, querying, analysing and reporting valuable information, final users have special tools that access data warehouses and datamarts (even transactional data), and these tools access the data dictionaries for document and inform to users what is the accessed data and which is its meaning.

Information Distribution and Control: Regular reports, news and other information must be delivered in a timely and secure fashion to any selected way like email, mobile, web and others to appropriate personnel.

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3. BI Components

OLAP (On-line analytical processing):

It refers to the way in which business users can slice and dice their way through data using sophisticated tools that allow for the navigation of dimensions such as time or hierarchies. Online Analytical Processing or OLAP provides multidimensional, summarized views of business data and is used for reporting, analysis, modelling and planning for optimizing the business. OLAP techniques and tools can be used to work with data warehouses or data marts designed for sophisticated enterprise intelligence systems. These systems process queries required to discover trends and analyse critical factors. Reporting software generates aggregated views of data to keep the management informed about the state of their business. Other BI tools are used to store and analyse data, such as data mining and data warehouses; decision support systems and forecasting; document warehouses and document management; knowledge management; mapping, information visualization, Journal of Theoretical and Applied Information Technology and dash boarding; management information systems, geographic information systems; Trend Analysis; Software as a Service (SaaS).

Advanced Analytics:

It is referred to as data mining, forecasting or predictive analytics, this takes advantage of statistical analysis techniques to predict or provide certainty measures on facts. Corporate Performance Management (Portals, Scorecards, Dashboards): this general category usually provides a container for several pieces to plug into so that the aggregate tells a story. For example, a balanced scorecard that displays portlets for financial metrics combined with say organizational learning and growth metrics.

Real time BI:

It allows for the real time distribution of metrics through email, messaging systems and/or interactive displays.

Data Warehouse and data marts:

The data warehouse is the significant component of business intelligence. It is subject oriented, integrated. The data warehouse supports the physical propagation of data by handling the numerous enterprise records for integration, cleansing, aggregation and query tasks. It can also contain the operational data which can be defined as an updateable set of integrated data used for enterprise wide tactical decision-making of a particular subject area. It contains live data, not snapshots, and retains minimal history. Data sources can be operational databases, historical data, external data for example, from market research companies or from the Internet), or information from the already existing data warehouse environment. The data sources can be relational databases or any other data structure that supports the line of business applications. They also can reside on many different platforms and can

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contain structured information, such as tables or spread sheets, or unstructured information, such as plaintext files or pictures and other multimedia information. A data mart as described by (Inmon, 1999) is a collection of subject areas organized for decision support based on the needs of a given department. Finance has their data mart, marketing has theirs, and sales have theirs and so on. And the data mart for marketing only faintly resembles anyone else's data mart. Perhaps most importantly, (Inmon, 1999) the individual departments own the hardware, software, data and programs that constitute the data mart. Each department has its own interpretation of what a data mart should look like and each department's data mart is peculiar to and specific to its own needs. Similar to data warehouses, data marts contain operational data that helps business experts to strategize based on analyses of past trends and experiences. The key difference is that the creation of a data mart is predicated on a specific, predefined need for a certain grouping and configuration of select data. There can be multiple data marts inside an enterprise. A data mart can support a particular business function, business process or business unit.

A data mart as described by (Inmon, 1999) is a collection of subject areas organized for decision support based on the needs of a given department. Finance has their data mart, marketing has theirs, and sales have theirs and so on. And the data mart for marketing only faintly resembles anyone else's data mart.

BI tools are widely accepted as a new middleware between transactional applications and decision support applications, thereby decoupling systems tailored to an efficient handling of business transactions from systems tailored to an efficient support of business decisions. The capabilities of BI include decision support, online analytical processing, statistical analysis, forecasting, and data mining.

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4. Conclusion Business intelligence (BI) is a technology-driven process for analysing data and presenting actionable information to help corporate executives, business managers and other end users make more informed business decisions. BI encompasses a variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards and data visualizations to make the analytical results available to corporate decision makers as well as operational workers.

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