Brian BALSER Lamia BENKIRANE Jeralyn PASINABO Dave WILSON BUSINESS INTELLIGENCE ANALYTICS. Query, Analysis and Reporting Tools

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1 Brian BALSER Lamia BENKIRANE Jeralyn PASINABO Dave WILSON BUSINESS INTELLIGENCE ANALYTICS Query, Analysis and Reporting Tools MBA 664 April the 13th, 2009

2 TABLE OF CONTENTS 1. BUSINESS INTELLIGENCE...4 A) DEFINITION OF BUSINESS INTELLIGENCE... 4 B) BUSINESS INTELLIGENCE AND OPERATIONAL INFORMATION SYSTEMS... 4 C) THE BUSINESS INTELLIGENCE CYCLE... 7 D) QUERY, ANALYSIS AND REPORTING TOOLS HISTORY OF BUSINESS INTELLIGENCE...9 A) ORIGINS OF BI:... 9 B) THE MODERN FACE OF BI: RELEVANCE AND INFLUENCE OF BI ON ORGANIZATIONS A) TANGIBLE AND INTANGIBLE BENEFITS B) HOW CAN BI TOOLS FULFILL BUSINESS NEEDS? FUTURE OF BI, GOING FORWARD SOURCES Abstract

3 Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications support the activities of decision support, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. BI includes a set of concepts and methods to improve business decision making by using fact-based support systems. This report will provide a broad overview and a technical description of BI and what things can be accomplished with BI with a main focus on its analytical tools and technologies. It will also provide a demonstration of the capabilities of two important BI tools: Microstrategy 8 and ReportNet. Lastly, it will take a general look of its future applications. Introduction Business Intelligence puts the right information in the right hands at the right time. Smart use of information and information technology can be one of the most effective ways to gain a competitive advantage and thrive in times of change. Evidence-based decision-making is spreading rapidly throughout commercial, non-profit and public sector organizations. That trend is driving the need for more insightful, more accurate and faster decision support solutions built on business intelligence (BI) and data warehouse (DW) tools, analytic applications and related services. In today s struggling economy with competition controlling and shrinking the landscape, it is important to make sound business decisions based on complete data. With the proper Business Intelligent implementation, businesses can make decisions and feel comfortable that they are provided with the proper tools and data needed to believe in their decisions.

4 1. Business Intelligence a) Definition of Business Intelligence Business Intelligence (BI) is the set of methodologies, processes and tools that are used by corporations to gather, store, access, and analyze data to enable users to make better business decisions faster. The principal goal of BI is to increase performance and gain a competitive advantage in the market place. BI also enables an effective implementation of the strategy in the organization. Indeed, by setting agreed upon and understood Key Performance Indicators, the users at every level in the organization will make decisions that are aligned with the formulated strategy. b) Business Intelligence and operational information systems To understand BI, it is important to make the difference between the 2 systems present in organizations: the operational information systems (OIS) and the BI system. The OIS are basically the systems that gather, update, store, retrieve and archive data. The data is captured daily in different databases which are stored in the Relational Database Management System (RDBMS) that we learned in this class. These data represent a list of all the transactions or business events that occur in the organization. Some examples of OIS include the shipping, billing, inventory or Automatic Teller Machine (ATM) systems. Collectively, these OIS are called Online Transaction Processing (OLTP) systems. The OIS systems export the data to the BI systems that transform raw data into useful information by organizing in dimensions, hierarchies and measures for analysis. There are several dimensions that we should consider to distinguish these two types of information systems. Business scope The OIS focus on the analysis of one particular department in isolation from the others. Information sharing is difficult within this context. BI systems are more powerful since they integrate the interdependencies between the different departments and allow people to cooperate, share information and achieve common goals.

5 Business processes The OIS automate processes to improve efficiency. It imposes a structure to the business such as the same business activity is performed exactly the same way each time. OIS are stable and do not change or change but slowly over time. BI systems support decision making to improve effectiveness and are adaptable systems in essence. BI systems adapt to the business and are always changing to adapt to the changing market conditions and/or users needs. Data integration In an OIS environment, it is very common to have duplicate applications developed by different departments. For example, the accounting and the order department may both develop their own customer databases. This is wasteful because not only, it requires more storage space but it also increases the risks of inconsistencies between the different applications. BI provides an integrated view of the organization. For example, a user can look at the claims data, the billing data and at policy data all together at the same time to understand what is happening from different perspectives. Thus, BI systems definitely support and facilitate the decision making process. Types of data In OIS, the data is continually updated but it tracks only current transactions and do not keep history about the business. The duplication of applications creates the risks of using different KPIs for the same entities or worse, using KPIs that are not significant to the achievement of the goals of the organization. BI systems maintain several years of detailed transactions taken from the different OIS. However, they represent periodic snapshots of the business situation since the extraction is not continuous. The more interfaces or uploads from the different OIS to the data warehouse, the more updated the information is and the better it is to take the best decisions. BI systems also create new or derived data by summarizing and calculating transaction data to support the KPIs that have been chosen to track performance and remain focused on achieving the goals of the overall company. The dashboard is one of the BI tools that provides this level of information.

6 Quality of data OIS are developed by different departments independently and the data they contain is not all clean, error free and complete. BI relies on data warehousing which provides a unique and reliable source of information for and about the business. Data Warehousing ensures the completeness and correctness of the data when taking the data from the various OIS. Indeed, before uploading or interfacing the data from the various OIS to the data warehouse, the technical teams make sure that the data is cleaned and as accurate and as complete as possible. Time frame In an OIS environment, OIS focus on providing reports according to the past performance. The organization reacts to the data that are shown in the reports. In a BI environment, the organization is proactive rather than reactive. BI tools, on top of giving information about past and current performance, allow the forecasting of what may happen in the future and take the according actions to make the change happen in the organization Timeliness: The huge amount of data and the lack of structure of the OIS make it difficult for the users to access the relevant information timely. They cannot visualize it and this prevents them from taking the best decisions timely. In the BI environment, the metrics shown in the analytical tools make it easier for the users to analyze the data and identify anomalies or trends for example that can provide knowledge to make plans proactively. Range of users: In an OIS context, users are dependent on the IT department to create and provide custom reports for them. Performance dashboards meet the needs of most users in the organization.

7 For all the reasons mentioned above, it is hard to get all the information needed from the OIS. Indeed, operational systems are not integrated and therefore do not provide an overall view of the organization. Operational systems are limited. They do not provide as much information as do the BI system which keeps track of years of data. It takes a lot of time for IT to create a custom report for them and it is sometimes too late to get the information needed and take their decisions quickly enough. Finally, Analytical tools in BI systems provide insights and make useful connections between data to the analysts that they would not have been able to see within an OIS configuration. c) The Business Intelligence Cycle Events Wisdom Review, Measure, Refine Action Experience Operational Systems Plans Knowledge Rules and Models Analytical Tools data Information Data Warehouses Analytical Systems Data to Information Business events are recorded in the operational or transactional systems as soon as they occur. In the BI environment, the data is extracted from the different OIS to create a single and common database for the organization. It is the data warehouse that represents the principal foundation for BI. It gives an integrated view of the organization and turns the data into information by providing a context to the data, cleaning it and structuring it in a meaningful way. Information to Knowledge Then, the users can turn this information into knowledge by using the various analytical tools of BI such as the query and reporting tools. The user is empowered to make analysis on the information given by identifying trends, patterns, or anomaly to take the best informed decisions and gain knowledge from it.

8 Knowledge to Rules Once the user understands these trends, patterns, or anomaly, he can share it with others in the organizations. If they are accepted and understood, they become the rule in the organization and each time a user is faced with this configuration in the future, he knows what to do! An example of a rule would be: Order 100 new units as soon as the inventory falls below 25 of a specific raw material Rules to Action BI has the ability to interpret transactions and anticipate results rather than only being reactive to events. Thanks to the analytical part of BI, the user is able to act on the data and be proactive. Thus, the objective of BI is enabling the users to track the performance, take fact based decisions faster and be proactive. BI allows the users to transform knowledge and rules into action by taking fact based decisions quickly. The focus is made on the alignment of the business activities with the global strategy by setting aligned metrics to track performance. Feedback loop Once the user implements an action plan, it will generate business events captured by the operational systems repeating the process. With experience, the organization is enabled to implement the best decisions and gain a competitive advantage by being a learning organization with a continuous improvement mindset. d) Query, Analysis and Reporting Tools Query, Analysis and Reporting tools provide the ability to any user at every level in the organization including the strategic, the tactical and the operational ones to analyze the data. They enable delivery of fast and efficient multidimensional analysis and answering business questions at the speed of thought. These questions could be: What is the profitability by product and by customer? What are the actual sales compared to the forecasted sales by period by region by salesperson by product? Thanks to the analytical tools also called Online Analytical Processing (OLAP), the user is enabled to see if there is any gap between what have been forecasted and what

9 have been realized for instance. Does this discrepancy occur in a specific region or is it a general tendency? Is it due to a particular salesperson or are they all involved? Or for instance, does one particular product has performed particularly well in a specific region? It is good to understand why and take actions by implementing the same methodologies or best practices in other regions for example. These tools present the data in reports where the user can choose the dimensions, slice and dice the data, filter by region or by product for instance, drill down and drill across at the speed of thought to identify the trends, patterns or anomalies and take informed decisions quickly. 2. History of Business Intelligence a) Origins of BI: The origins of business intelligence may be traced back to the first data processing applications, which were simple applications such as accounts payable and receivable in the early 1990s. These applications ran on sequential technology, such as magnetic and paper tapes. Using sequential media for storage meant the entire file had to be accessed, even if only a fraction of the file was needed. Oxide often stripped off of magnetic tapes, and entire files were lost. These issues led to the need for a new way to analyze information. By the early 1990s, BI consisted of two nascent segments: data warehousing and desktop query and reporting tools. At the time, users needed to know SQL to submit queries. In the late 1990s, these desktop query and reporting tools were converted to the web and bundles with other types of analytical tools to create what are today called BI suites or BI platforms. b) The modern face of BI: In broader sense, BI encompasses a raft of data warehousing and data integration technologies as well as query, reporting, and analysis tools required fulfilling the promise of giving business users self-service access to information. Performance dashboards represent the latest incarnation of BI, the modern face of BI; they are built on years of technical and process innovation within the BI field and span both the data management and analytical sides of BI.

10 3. Relevance and Influence of BI on organizations a) Tangible and Intangible Benefits There are two general types of benefits that can be realized with the utilization of a Business Intelligence solution. These benefits can be tangible which has a quantifiable measurement of value given to the Business Intelligence solution in relationship to how it affects the bottom line. While a benefit thought to be intangible may have a great impact on an organization without showing its effect on the bottom line. Tangible benefits are much easier to see and sell to upper management as they can illustrate the potential impact on profitability resulting from either revenue generation or cost reduction. An example of a tangible benefit to an organization would be increased revenue from new sales by new customers. These new customers may have come about in response to mailings generated from BI reports through improved targeting. Being able to obtain a target market and then capitalize on that market would be a great way to illustrate a tangible benefit of any Business Intelligence solution. Another example of a tangible benefit derived from a Business Intelligence solution would be the organization s ability to track their suppliers and streamline their production department. By getting these two aspects in synch an organization can: Decrease raw material costs due to improved supplier management and negotiation Reduce defect rates Reduce inventory carrying costs or manufacturing overproduction Reduce time to market for new products Improve pricing policies based on more complete revenue and cost information These are just a few examples of how a Business Intelligence solution can provide tangible benefits. Not every business will realize the same benefits, but every business will realize some tangible benefit. One of the biggest tangible benefits of a Business Intelligence solution is the ability for employees to access data in a timely manner. When employees have access to information, the ability to sort

11 information quickly, and the assurance that the data is accurate and standardized, these employees are much more equipped to make real decisions and not be buried in paperwork. The time savings are worth a lot of money in terms of salaries and enable the organization to make tremendous cost savings. This access to formatted information also allows employees to make decisions based on facts rather than flying blind. Employees cannot only make more informed decisions they have the ability to have a faster response to changing conditions with plenty of data to support market trends. Intangible benefits are definitely worth noting because they provide value to the organization as a whole but they do not easily convert into a financial metric that can be translated to impact on an organization s bottom line. When an employee has all the information they need in a timely manner, they then have the ability to make sound decisions very quickly. This will tend to create happy customers who feel that their needs are being attended to. With the onset of happy customers and employees feeling empowered to make the correct decisions for their customers, you have happy employees. Happy employees represent an intangible benefit any organization can hope for because happy employees tend to work harder with a sense of accomplishment and will highly contribute to increase performance as a result. Similarly, a happy customer will tend to come back to buy products or services and tell his friends! A study done by the Data Warehousing Institute in 2003 on a sample of 510 companies gave the following results:

12 It is interesting to note that BI mostly delivers intangible benefits which makes the investment on it more challenging to justify (since most of its benefits are not quantifiable). The highest % of respondents think that the benefits of BI are intangible. 55% of respondents think that BI delivers more efficient processes. 56% of respondents think that BI delivers the ability to have better tactics and take better decisions. 57% of respondents think that BI delivers the ability to have better strategies and plans and 59% of respondents think that BI delivers a single version of the truth. b) How can BI tools fulfill business needs? With the advent of relatively inexpensive computer hardware and storage devices, more and more organizations have more than enough data to make informed decisions. Unfortunately most of today s organizations have kept so much data that sorting through it has become unimaginable. An application that can mine through data, sort it by relevance, and make it easy to digest can be a literal lifesaver to that organization. One example that comes to mind is that of an organization who was not looking for ways to make more money, but was looking for ways to make their city safer. The Richmond, Va. Police department had plenty of data on who, what, when, where, and why crimes were being committed, but they had so much data that attempting to trend it became an almost insurmountable task. In 2005, the Richmond Police Department brought a Business Intelligence solution online under much scrutiny from the residence of Richmond. After being able to analyze crime reports and cross reference them with conditions such as weather patterns, sporting event schedules, the Richmond Police Department boasted a 20% drop in the crime rates across the board. This was attributed to their ability to predict when and where a crime may be committed and adjusting patrol routes to accommodate their predictions. Any organization in existence can benefit from being able to trend markets and predict where the next big ticket item will surface. It is information like this that will eventually start to segregate organizations into proactive trend setters and reactive trend followers.

13 4. Future of BI, Going Forward Research shows that although business analytics solutions are not new, only now are they entering the mainstream. The market, which seems to be moving in 15-year cycles, continues to evolve by incorporating new components into business analytics solutions. What started out as standalone batch reporting and statistics tools have matured into broad suites of components that address data integration, data warehousing, query and reporting, advanced analytic and other related decision support components. One of the paradigm shifts noted in recent years is moving beyond simple reporting to proactive analysis of the data and providing prescriptive recommendations on how to interpret the data. This, of course, relies on the fact that corporations can successfully move from caring about what happened in the past to a desire to not only know what s wrong but what is likely to get worse if nothing is done. That is where the power of advanced analytics plays such a powerful role. What lies ahead if the leap can be made that tools like reporting, querying, OLAP, dashboards, scorecards and portals can be successfully used to help make sense of the world around us? There is a concept called the next generation of BI, which focuses on empowering users to freely access and share the information most relevant to their needs. BI should not only do what we ve been promised to date (ubiquitous information at your fingertips) but also just in time (aka realtime BI) and BI should necessarily involve a collaboration component making BI part of the factbased decision system where facts come from tacit and explicit data sources. A corporation s foreknowledge comes from a comprehensive look at all the available data. This can only be accomplished through a strong technological strategy built around reliable tools. Gaining an understanding of BI will move any company from simply delivering reports to enabling interactive analysis and information sharing. When BI is integrated into everyday business processes, corporations stay focused on what to achieve, not only what has been accomplished. Organizations embarking on or continuing their path toward BI need to decide how to allocate their scarce human, capital and IT resources to tasks and projects that have the biggest impact on increasing the diffusion of BI throughout their organizations and to external stakeholders.

14 5. Sources Vitt, Elizabeth, et. Al., Business Intelligence: Making Better Decisions Faster, Microsoft Press, USA, Eckerson, Wayne W., Performance Dashboards: Measuring, Monitoring, and Managing Your Business, John Wiley and Sons, New Jersey, Biere, Mike, Business Intelligence for the Enterprise, The Impact of Business Intelligence, Illustrated Ed., Prentice Hall (PTR), New Jersey, 2003, pp Raisinghani, Mahesh S., Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks, Illustrated Ed., Idea Group Inc (IGI), Pennsylvania,