M15 Review Questions (Rq) Business Intelligence and Big Data Kroenke Book Chap 12

Using Direction Information Systems David Kroenke Business Intelligence and Knowledge Management Affiliate 9 © 2007 Prentice Hall, Inc. 1

Learning Objectives Empathize the need for business intelligence systems. Know the characteristics of reporting systems. Know the purpose and office of information warehouses and data marts. Sympathise fundamental data-mining techniques. Know the purpose, features, and functions of knowledge direction systems. 2

The Nature of Intelligence Some of the characteristics of intelligent beliefs include the ability to do the following: Learn from experience including the power to learn by trial and error Apply knowledge acquired from experience to another situation Handle complex situations Solve issues when of import information is missing is the essence of decision making when dealing with uncertainty Determining what is important is a mark of a good decision maker The power to reason and think Reacting speedily and correctly to a new situation Empathise interpret visual images including processing and manipulating symbols Being creative and imaginative Using heuristics, or rules of thumb, or fifty-fifty guesses in making decisions 3

What is AI? Bogus Intelligence systems include people, procedures, hardware, software, information and knowledge needed to develop computer systems and machines that demonstrate characteristics of intelligence [Ralph Stair]. four

Components of AI Expert Systems are calculator programs that act or behave similar a human being expert in a field or area. Robotics involves developing mechanical or computer devices controlled by software to perform tasks that crave a loftier degree of precision or are wearisome or hazardous for humans Vision Systems include hardware and software that permit computers to capture, store and manipulate visual images and pictures Tongue Processing allows the estimator to understand react to statements and commands fabricated in a "natural" linguistic communication, such as English Learning Systems include hardware and software that allow the computer to change how it functions or reacts to situations based on feedback it receives Neural Networks are reckoner systems that human action like or simulate the functioning of the human brain 5

Skilful Systems l l l Proficient systems are created by interviewing experts in a given business domain and codifying the rules stated by those experts. Many proficient systems were created in the late 1980 south and 1990 southward, and some of them have been successful. Adept systems suffer from three major disadvantages. l They are difficult and expensive to develop. l They are difficult to maintain. l They were unable to live upwardly to the high expectations gear up past their proper noun. 6

The Demand for Business Intelligence Systems According to a study done at the University of California at Berkeley, a total of 403 petabytes of new data were created in 2002. 403 petabytes is roughly the corporeality of all printed material ever written. l 50 The printed collection of the Library of Congress is. 01 petabytes. 400 petabytes equals 40, 000 copies of the impress collection of the Library of Congress. 7

Concern Intelligence Systems The purpose of a business intelligence (BI) system is to provide the right information, to the right user, at the right time. BI systems aid users accomplish their goals and objectives by producing insights that pb to actions. eight

Business Intelligence Tools for searching business data in an attempt to find patterns is chosen business intelligence (BI) tools. The processing of data is simple: Information are sorted and grouped and simple totals and averages are calculated. Reporting tools are used to address questions like: l l l What has happened in the past? What is the electric current state of affairs? How does the current state of affairs compare to the past? Data-mining tools process data using statistical techniques, many of which are sophisticated and mathematically complex. Data mining involves searching for patterns and relationships among data. In most cases, data-mining tools are used to make predictions. l For example, we can apply i course of analysis to compute the probability that a customer will default on a loan. Data-mining tools use sophisticated techniques. 9

Data Mining Information mining is the application of statistical techniques to notice patterns and relationships among data and to classify and predict. Information mining represents a convergence of disciplines. Data-mining techniques emerged from statistics and mathematics and from artificial intelligence and motorcar-learning fields in reckoner science. 10

Unsupervised Information Mining With unsupervised information mining, analysts do non create a model or hypothesis before running the assay. Instead, they apply the data-mining technique to the information and notice the results. Analysts create hypotheses afterwards the analysis to explain the patterns found. eleven

Supervised Data Mining With supervised data mining, data miners develop a model prior to the analysis and apply statistical techniques to data to approximate parameters of the model. One such analysis, which measures the touch on of a set of variables on another variable, is chosen a regression analysis. Neural networks are another popular supervised data-mining technique used to predict values and brand classifications such as "proficient prospect" or "poor prospect" customers. 12

Information Warehouses and Data Marts Basic reports and simple OLAP analyses can be made direct from operational data. Many organizations cull to excerpt operational information into facilities chosen data warehouses and data marts, both of which are facilities that set, store, and manage data specifically for data mining and other analyses. Programs read operational information and extract, clean, and prepare that data for BI processing. The prepared data are stored in a data-warehouse database using data-warehouse DBMS, which can be different from the organization'south operational DBMS. thirteen

Information Warehouses Versus Data Marts A data mart is a information collection, smaller than the data warehouse, that addresses a particular component or functional area of the business. The data warehouse is like the distributor in the supply chain and the data mart is like the retail store in the supply chain. Users in the data mart obtain data that pertain to a particular business function from the data warehouse. It is expensive to create, staff, and operate data warehouses and information marts. fourteen

Problems with Operational Data Near operational and purchased data accept problems that inhibit their usefulness for business intelligence. 15

Decision Trees A decision tree is a hierarchical arrangement of criteria that predict a classification or a value. Decision tree analyses are an unsupervised datamining technique. The analyst sets up the calculator plan and provides the information to clarify, and the determination tree plan produces the tree. 16

A Decision Tree for Loan Evaluation A mutual business organisation application of conclusion copse is to classify loans by likelihood of default. Organizations analyze data from past loans to produce a conclusion tree that tin be converted to loan-determination rules. l A fiscal institution could apply such a tree to assess the default risk on a new loan. 17

Reporting Systems The purpose of a reporting system is to create meaningful information from disparate data sources and to deliver that information to the proper user on a timely basis. Reporting systems generate information from data equally a upshot of 4 operations: l l Filtering information Sorting data Group information Making uncomplicated calculations on the data 18

Components of Reporting Systems A reporting system maintains a database of reporting metadata. The metadata describes the reports, users, groups, roles, events, and other entities involved in the reporting action. The reporting organization uses the metadata to prepare and evangelize reports to the proper users on a timely footing. xix

Written report Type In terms of a report type, reports can be static or dynamic. Static reports are prepared in one case from the underlying data, and they do not change. fifty Example, a report of past yr'due south sales Dynamic reports: the reporting system reads the nigh current information and generates the report using that fresh data. Examples are: a study on sales today and a written report on current stock prices Query reports are prepared in response to data entered past users. Online belittling processing (OLAP) reports allow the user to dynamically modify the report grouping structures. 50 20

Report Media Reports are delivered via many different report media or channels. Some reports are printed on paper, and others are created in a format like PDF whereby they tin be printed or viewed electronically. Other reports are delivered to reckoner screens. Companies sometimes place reports on internal corporate Web sites for employees to access. Another report medium is a digital dashboard, which is an electronic display customized for a particular user. l 50 l Vendors similar Yahoo! and MSN provide common examples. Users of these services can define content they desire- say, a local atmospheric condition forecast, a list of stock prices, or a list of news sources. The vendor constructs the display customized for each user. 21

Digital Dashboard Example 22

RFM Analysis RFM analysis is a way of analyzing and ranking customers according to their purchasing patterns. It is a elementary technique that considers how recently (R) a client has ordered, how ofttimes (F) a customer orders, and how much money (M) the customer spends per club. To produce an RFM score, the program first sorts customer purchase records past the date of their most recent (R) purchase. In a mutual class of this analysis, the program then divides the customers into v groups and gives customers in each group a score of 1 to 5. l The summit 20% of the customers having the most recent orders are given an R score ane (highest). The program then re-sorts the customers on the basis of how oft they order. l The tiptop twenty% of the customers who club most oftentimes are given a F score of 1 (highest). Finally the program sorts the customers again co-ordinate to the amount spent on their orders. fifty The 20% who take ordered the virtually expensive items are given an M score of 1 (highest). 23

Online Analytical Processing Online analytical processing (OLAP) provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data. The remarkable characteristics of OLAP reports is that they are dynamic. The viewer of the report tin modify the study's format, hence, the term online. An OLAP study has measures and dimensions. A measure is the data item of interest. l It is the item that is to be summed or averaged or otherwise processed in the OLAP report. A dimension is a characteristic of a measure. Buy data, customer type, customer location, and sales region are all examples of dimension. With an OLAP study, it is possible to drill down into the data. l l This term means to further divide the data into more particular. 24

Market-Basket Analysis A marketplace-handbasket analysis is a data-mining technique for determining sales patterns. A market-basket analysis shows the products that customers tend to buy together. In marketplace-basket terminology, support is the probability that two items will be purchased together. You can expect market-basket assay to become a standard CRM analysis during your career. 25

Knowledge Direction Noesis management systems concern the sharing of knowledge that is already known to be, either in libraries of documents, in the heads of employees, or in other known sources. Cognition management (KM) is the process of creating value from intellectual capital and sharing that knowledge with employees, managers, suppliers, customers, and others who demand that capital letter. Cognition management is a process that is supported by the v components of an information system. l Its emphasis is on people, their knowledge, and constructive means for sharing that knowledge with others. The benefits of KM concern the application of knowledge to enable employees and others to leverage organizational knowledge to work smarter. KM preserves organizational memory by capturing and storing the lessons learned and best practices of central employees. 26

Content Management Systems Content direction systems are information systems that rails organizational documents, Web pages, graphics, and related materials. KM content management systems are concerned with the creation, management, and delivery of documents that exist for the purpose of imparting knowledge. Typical users of content management systems are companies that sell complicated products and want to share their knowledge of those products with employees and customers. The basic functions of content management systems are the same as for report management systems: author, manage, and evangelize. The only requirement that content managers place on document authoring is that the document has been created in a standardized format. 27

Content Delivery Almost all users of content direction systems pull the contents. Users cannot pull content if they exercise not know information technology exists. l The content must be arranged and indexed, and a facility for searching the content devised. Documents that reside behind a corporate firewall, nevertheless, are non publicly attainable and will not be reachable by Google or other search engines. Organizations must index their own proprietary documents and provide their ain search capability for them. Web browsers and other programs tin can readily format content expressed in HTML, PDF, or another standard format. XML documents often contain their own formatting rules that browsers can interpret. l l The content management organisation will have to determine an appropriate format for content expressed in other ways. 28

KM Systems to Facilitate the Sharing of Homo Knowledge Nothing is more frustrating for a managing director to contemplate than the state of affairs in which one employee struggles with a problem that another employee knows how to solve easily. KM systems are concerned with the sharing not only of content, simply too with the sharing of knowledge among humans. How can one person share her knowledge with another? l How can 1 person learn of some other person's great thought? Three forms of engineering science are used for knowledge- sharing amongst humans: 50 l Portals, discussion groups, and email Collaborations systems Expert systems 29

Ethics Guide–The Ideals of Classification is a useful human skill. Sorting and classifying are necessary, important, and essential activities. l Merely those activities can besides be unsafe Serious ethical issues arise when we classify people. fifty l 50 What makes someone a good or bad "prospect"? If we're talking nigh classifying customers in order to prioritize our sales calls, then the ethical event may non be besides serious. What well-nigh classifying applicants for college? xxx

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