Business Intelligence & its Best Practices
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This document discusses business intelligence and best practices for implementing business intelligence projects. It begins with defining business intelligence as processes, tools, and technologies that help transform data into useful information to improve business decision making and profitability. It then discusses important concepts like data warehousing and analytics. The document concludes by outlining some best practices for prioritizing and successfully implementing business intelligence initiatives like understanding business needs, ensuring data quality, selecting appropriate tools, and ongoing training.
Business Intelligence & its Best Practices
- 1. Business Intelligence & Its Best Practices Transforming Data into Analytics Wednesday, May 12, 2010 May 2010, issue ABSTRACT P.1 Business Intelligence ? P.2 Best Practices P.3 ABSTRACT Next Generation Business Model- ing is putting Intelligence into Busi- ness solutions. The first era of busi- ness solution is over. The next gen- eration of business solutions with integrated intelligence is here and it will focus on the business user About Author putting the personal "I" in "IT" as never before which will read as Rajan Kumar Upadhyay, Research Analyst Intelligent Information Technology (IIT). Rajan Kumar Upadhyay has over 10 years of leadership experience in the development of software and IT business and total enterprise solutions and has held executive level positions at companies Read more for such as GAUSA India, NGBM. He has used his expertise in business solutions consulting to assist other well-respected companies such as SAP, Cisco, Reliance, BSNL , Juniper networks, Synergy Re- • What is Business Intelli- search Group, ACG Research etc. gence? Rajan’s experience with both the software product business and the IT service business is the under- • Importance of Business Intel- pinning of his business philosophy and vision: Find the best talent and expertise to produce the most ligence innovative products and services and work with global enterprises to deploy those solutions. With collective intelligence of approx 24000 hrs , Rajan is using his knowledge of architecture and data- • Integration of Intelligence in base design to lead development and deployment of innovative, next-generation project manage- Business Modeling from Su- ment tools, resources, and services. perior Analytics Rajan earned Master’s Degree in Computer Application. • Interactive Analysis En- hances Business Intelligence Data.
- 2. What is Business Intelligence ? The next generation of business solutions with integrated intelligence is here and it will focus on the business user putting the personal "I" in "IT" as never before which will read as Intelligent Information Technology (IIT). data mining , business performance man- Business Intelligence (BI) is a terminology agement, benchmarking, text mining, and Integration of Intelligence in representing a collection of processes, predictive analytics. tools and technologies helpful in achieving Business Modeling from Su- Business Intelligence often aims to support perior Analytics. more profit by considerably improving the better business decision-making. Thus a BI productivity, sales and service of an enter- system can be called a decision support As the volume of business intelli- prise. With the help of BI methods, the system (DSS). Though the term business gence available to the enterprise corporate data can be organized, analyzed intelligence is often used as a synonym for grows every day, users are burdened in a better way and then converted into an competitive intelligence, because they with the task of trying to make sense useful knowledge of information needed both support decision making, BI uses of it all. Intelligent Business solutions to initiate a profitable business action. technologies, processes, and applications provide a great deal of cost-effective Thus its about turning a raw, collected data to analyze mostly internal, structured data assistance in collecting and organiz- into an intelligent information by analyzing and business processes while competitive ing data, and offer standardized and re-arranging the data according to the intelligence, is done by gathering, analyz- reports for analyzing information. relationships between the data items by ing and disseminating information with or When those solutions which are knowing what data to collect and manage without support from technology and ap- typically rigid in their application, and in what context. plications, and focuses on all-source infor- users come up with questions not mation and data (unstructured or struc- covered by a pre-defined report. So Importance of Business Intelligence: they must either rely on expert or IT tured), mostly external to, but also internal A company's collected raw data is an im- resources to help develop custom- to a company, to support decision mak- portant asset where one can find solutions ized reports, or cobble together ing... their own custom report through to many of an organization’s critical ques- spreadsheets and other rudimentary tions like 'what was the net profit for a tools at their disposal. This kind of particular product last year and what will inefficiency has consequences when be sales this year and what are the key the stakes are high and the competi- factors to be focused this year in order to tion is tight, the ability to analyze increase the sales?'. So there arises a ne- data quickly is imperative. There- cessity of a well planned BI system which fore, users need business solutions can lead to a greater profitability by reduc- with self analytics tool or intelligent ing the operating costs, increasing the business solutions that provide a far sales and thereby improving the customer greater flexibility in understanding satisfaction for an enterprise. Business Intelligence is Intelligent valuable information’s. With the help of a Business Intelligence Business System, a company may improve its busi- Business Intelligence is not just about ness or rule over its competitors by explor- technology and cannot be effective in ing and exploiting its data to know the cus- isolation. To live and breath it needs to tomer preferences, nature of customers, supply chains, geographical influences, be part of a broader framework cover- pricings and how to increase its overall ing the questions that its users need to business efficiency. answer, the actions that they take based on these answers and the itera- BI technologies provide historical, current, tive learning that occurs in the process. and predictive views of business opera- tions. Common functions of Business Intel- ligence technologies are reporting, online analytical processing, analytics,
- 3. Business Intelligence :: Continued Business intelligence & data warehousing Often BI applications use data gathered from a data warehouse or a data mart. However, not all data warehouses are used for busi- ness intelligence, nor do all business intelligence applications require a data warehouse. Business intelligence refers to systems and technologies that provide the business with the means for decision-makers to extract personalized meaningful information about their business and industry, not typi- cally available from internal systems alone. This includes advanced decision sup- port tools and back-room systems and databases to support those tools. The data warehouse is that back-room database. Combine that with the support tools required to build and maintain the data warehouse, such as data cleansing and extract, transform and load tools and you have what many call data ware- housing. Think of the data warehouse as the back office and business intelligence as the entire business including the back office. The busi- ness needs the back office on which to function, but the back office without a business to support, makes no sense Business intelligence and business analytics Business intelligence should be divided into querying, reporting, OLAP, an "alerts" tool, and business analytics. Querying, reporting, OLAP always gives you real time data information. Business analytics makes extensive use of these datas, statistical and quantita- tive analysis, explanatory and predictive modeling , and fact-based management to drive decision making. Analytics may be used as input for human decisions or may drive fully automated decisions. Business intelligence is querying, reporting, OLAP, and "alerts". In other words, querying, reporting, OLAP, and "alert" tools can answer the questions: what happened; how many, how often, where; where exactly is the problem; what actions are needed. Business analytics can answer the questions: why is this happening; what if these trends continue; what will happen next (that is, predict); what is the best that can happen (that is, optimize). Getting Business Intelligence projects prioritized It is often difficult to provide a positive business case for Business Intelligence (BI) initiatives and often the projects will need to be prioritized through strategic initiatives. Here are some hints to increase the benefits for a BI project. • You must determine the tangible benefits such as eliminated cost of producing legacy reports. • Enforce access to data for the entire organization. In this way even a small benefit, such as a few minutes saved, will make a difference when it is multiplied by the number of employees in the entire organization. • Consider letting the BI project be driven by other business initiatives with excellent business cases. To support this approach, the organization must have Enterprise Architects, which will be able to detect suitable business projects.
- 4. Critical Success Factors of Business Intelligence Implementation: Although there could be many fac- tors that could affect the implemen- tation process of a BI system, re- search shows that the following are the critical success factors for busi- ness intelligence implementation: Best Practices with Business Intelligence In the current competitive era, It makes cru- approaches, from the traditional method to 1. Business-driven methodology & ask the people what they want, also looking project management cial for Analyst to implement a Business In- telligence project because of complexity of for study how the processes work through 2. Clear vision & planning business & quick turn around on decisions. the company, how the people work, how they make decisions, which information they 3. Committed management support Its not easy because you need to adopt & sponsorship need to make decisions and when they need some best practices to achieve implement a those information. The IT and the business 4. Data management & quality successful BI. need to develop together a business-focused 5. Mapping solutions to user re- Implementation of successful BI can be metadata that provide all the business re- quirements achieved with following steps quirements. 6. Performance considerations of the BI system 1) Understand Business issues : First of all, 4) Competency Analysis: Setup a team for you need understand your business issues Competency analysis, This will gather basic 7. Robust & expandable framework before implement your BI, aligning the busi- data on how your competitors do business, ness goals with the BI strategy, creating a What are your Competency Strategy. solid partnership with business and IT. 5) Data Quality: It is very important to check 2) BI, a continuous process : Remember BI is the data quality in the source systems before not a project but a continuous process to start the BI development, because one of delivery better information to the company the main keys of success to a well imple- make better decisions. Before you start mented BI is the data quality. process with BI, Please make sure you have enough balance of credits and executive 6) Selecting BI Tools: sponsor. BI processes may be little costly Choose carefully your BI Tools, looking for standardization. Of course, you can and deal while its implementation but always should choice a BI vendor to front-end, and others to the back-end as data warehouse give better future results. platform or ETL tool. The standardization is mainly in the BI front-end tools (query, re- porting and analysis); you should choice only one BI suite of tools that attend all the BI is important to set target goals and refor- front-end requirements. What you shouldn't buy different tools from the different ven- mation of company strategy dors to the same area of BI, like to buy multiple reporting or query tools. 3) Requirement Gathering: When you are Ongoing training the users on the BI tools and how to use better the data in the tools, gathering business requirements, you should also offering the right BI tool to the right user group, recognizing the importance of BI to talk with persons in different levels of the front-end tools in attracting the users. company, You should document what you Always keep in your mind that Business Intelligence has to delivery the right informa- learned in the meeting. You should keep the tion when it is required, in the right format, in the right time to the right people. scope of your DW/BI requirements process. During the process, you should use many