Chapter 9

This chapter considers business intelligence (BI) systems: information systems that can produce patterns, relationships, and other information from organizational structured and unstructured social data as well as from external, purchased data. BI systems to identify patterns, relationships, and other information in organizational structured and unstructured social data, as well as purchased external data. In addition to this data, another rich source of knowledge is employees themselves. Including, vast amounts of collective knowledge exist in every organization’s employees. Business intelligence is the key technology supporting such marketing technology.

Q1: How do organizations use business intelligence (BI) systems?

BI systems are information systems that process operational and other data to identify patterns, relationships, and trends for use by business professionals and other knowledge workers. Five standard IS components are present in BI systems: hardware, software, data, procedures, and people. The boundaries of BI systems are blurry. Typical Uses for BI, identifying changes in purchasing patterns, important life events change what customers buy, entertainment and Netflix has data on watching, listening, and rental habits. Classify customers by viewing patterns, predictive policing and analyze data on past crimes - location, date, time, day of week, type of crime, and related data. Just-in-Time Medical Reporting, Example of real time data mining and reporting. Injection notification services, software analyzes patient’s records, if injections needed, recommends as exam progresses and blurry edge of medical ethics.

Q2: What are the three primary activities in the BI process?

These activities directly correspond to the BI elements and the four fundamental categories of BI analysis are reporting, data mining, BigData, and knowledge management. Push publishing delivers business intelligence to users without any request from the users; the BI results are delivered according to a schedule or as a result of an event or particular data condition. Pull publishing requires the user to request BI results. Data broker/aggregator acquires and purchases consumer and other data from public records, retailers, Internet cookie vendors, social media trackers, and other sources. Data for business intelligence to sell to companies and governments

Q3: How do organizations use data warehouses and data marts to acquire data?

For a small organization, the extraction may be as simple as an Access database. Larger organizations, however, typically create and staff a group of people who manage and run a data warehouse, which is a facility for managing an organization’s BI data. Functions of a data warehouse: obtain data from operational, internal and external databases. Also cleanse data, organize and relate data, catalog data using metadata. The components of a data warehouse. Programs read operational and other data and extract, clean, and prepare that data for BI processing. An organization might use Oracle for its operational processing, but use SQL Server for its data warehouse. Other organizations use SQL Server for operational processing, but use DBMSs from statistical package vendors such as SAS or SPSS in the data warehouse. Purchase of data about other organizations is not unusual or particularly concerning from a privacy standpoint.  However, some companies choose to buy personal, consumer data (like marital status) from data vendors like Acxiom Corporation. The data analysts who work with a data warehouse are experts at data management, data cleaning, data transformation, data relationships, and the like. However, they are not usually experts in a given business function. A data mart is a subset of a data warehouse. A date mart addresses a particular component or functional area of the business.

Q4: How do organizations use reporting applications?

A reporting application is a BI application that inputs data from one or more sources and applies reporting operations to that data to produce business intelligence. Create meaningful information from disparate data sources. Deliver information to user on time through basic operations: sorting, filtering, grouping, calculating and formatting. RFM considers how recently (R) a customer has ordered, how frequently (F) a customer ordered, and how much money (M) the customer has spent. Produce an RFM score, a program sorts customer purchase records by date of most recent (R) purchase, divides sorts into quintiles, and gives customers a score of 1 to 5. Process is repeated for Frequently and Money.

Q5: How do organizations use data mining applications?

Sources of discipline in data mining are AI machine learning, data management technology, sophisticated marketing, finance and other business professionals. Also cheap computer processing and storage, huge databases and statistical mathematics.  Unsupervised data mining consists of a hypothesis or model. Findings obtained solely by data analysis and hypothesized model created to explain patterns found. Cluster analysis is statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data. Supervised data mining uses a priori model and prediction such as regression analysis. Market-basket analysis is an identify sales patterns in large volumes of data, identify what products customers tend to buy together. Computes probabilities of purchases, identify cross-selling opportunities and ssociation analysis important part in shopping basket data analysis. Basic idea of a decision tree is to select attributes most useful for classifying entities. Select attributes most useful for classifying “pure group” and hierarchical arrangement of criteria to predict a value or classification.

Q6: How do organizations use BigData applications?

Big Data is a term used to describe data collections that are characterized by huge volume, rapid velocity, and great variety. Huge volume is a petabyte and larger then rapid velocity is generated rapidly. Great variety is structured data, free-form text, log files, graphics, audio, and video. Technique for harnessing power of thousands of computers working in parallel. BigData collection is broken into pieces, and hundreds or thousands of independent processors search these pieces for something of interest. BigData has volume, velocity, and variation characteristics that far exceed those of traditional reporting and data mining. Experts are required to use it; you may be involved, however, in planning a BigData study or in interpreting results.

Q7: What is the role of knowledge management systems?

Knowledge Management (KM) is creating value from intellectual capital and sharing knowledge with those who need that capital. Preserving organizational memory by capturing and storing lessons learned and best practices of key employees. Benefits of Knowledge Management is to improve process quality, increase team strength. The goal is to nable employees to use organization’s collective knowledge. Expert systems are rule-based systems that encode human knowledge as If/Then rules and programs that process a set of rules. The few expert systems that have been successful have addressed more restricted problems than duplicating a doctor’s diagnostic ability. They address problems such as checking for harmful prescription drug interactions and configuring products to meet customer specifications. These systems require many fewer rules and are therefore more manageable to maintain. Content Management Systems Support management and delivery of documents, other expressions of employee knowledge.

Q8: 2026?

In 2026, exponentially more information about customers, better data mining techniques. As companies buy and sell your purchasing habits and psyche. Singularity are when computer systems adapt and create their own software without human assistance. In the end, Machines will possess and create information for themselves