Using MIS Chapter 9 – Flashcards
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BI Systems
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systems that process operational and other data to identifie patterns, relationships, and trends for use among other workers and business professionals
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Business Intelligence
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patterns, relationships, trends, and predictions
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BI Application
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The software component of a BI system
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BI Systems are used for all four Collaborative tasks, name these 4 tasks:
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Project mgmt, problem solving, deciding, informing
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What are the three primary activities in the BI process?
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Data Aquisition, BI Analysis, Publishing results
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Data Aquisition
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process of obtaining, cleaning, organizing, relating, and cataloging source data
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BI Analysis
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process of creating business intelligence through reporting, data mining, and knowledge mgmt
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Push Publishing
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delivers BI without reguest from user
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Pull Publishing
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requires user to request BI
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Data Warehouse
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facility for managing an organizations BI data (larger than data mart)
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four functions of a Data warehouse
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obtain, clense, organize, catalog
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Problems with operational data (6)
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dirty data, missing values, inconsistent data, data not integrated, wrong granularity, too much data
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granularity
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refers to the level of detail represented by the data
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Data Mart
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smaller than a data warehouse, and addressed the needs of a particular department or functional area of a business
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reporting application
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a BI tool that inputs data from one or more sources and applies reporting operations to that data to produce Business Intelligence
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5 basic reporting operations
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sorting, filtering, grouping, calculating, formatting
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RFM Analysis
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reporting technique that considers how RECENTLY a customer has ordered, how FREQUENTLY they order, and how much MONEY the spent.
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Online Analytical Processing (OLAP)
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reporting technique that provides the ability to sum, count, average, and perform other simple arithmatic operations on a group of data, OLAP reports are dynamic, meaning viewers can change the format.
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Measure
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data item of interest
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Dimension
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characteristic of a measure
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Drill Down the Data
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to further divide the data into more detail
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Data Mining
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The application of statistical techniques to find patterns and relationships amaong data for classifications and prediction.
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6 Data Mining Origins
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Statistics/mathmatics, artificial intelligence machine learning, huge database, cheap computer processing and storage, sophisticated marketing, finance and other professionals, data mgmt technology.
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unsupervised data mining
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analysts do not create a model or a hypothesis before running the analysis
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Cluster analysis
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type of unsupervised data mining, identifies groups of entities that have similar characteristics
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Supervised data mining
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data miners develop a model prior to the analysis and estimate parameters for the model
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regressional analysis
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type of supervised data mining, measures the impact of one set of variables on another
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Neutral networks
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type of supervised data mining, predicts values and makes classifications such as "good prospect" and "poor prospect"
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Market Basket Analysis
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unsupervised data mining technique for determing sales patterns, shows the products that customers tend to buy together
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Cross selling
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"If somone buys X, sell them Y. If someone buys Y, sell them X."
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Support
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The porbability that two items will be purchased together
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Confidence
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probability estimate of buying and item
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Lift
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probability of buying X without Y
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Descision Tree
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hierarcheal arrangement of criteria that predict a classification or a value, creates groups that are as "pure" as possible using "if/then" statements to create rules
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Knowledge Management (KM) Systems
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The process of creating value from intellectual capital and sharing that knowledge with others who need it
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Primary bennefits of KM
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1. fosters innovation by encouraging free flow of ideas 2. provides customer service by streamlining response time 3.boosts revenue by getting products to market faster 4. enhances employee retention by recognizing and rewarding them 5.streamlines operations & reduces costs by eliminating uneccesary processes
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Indexing
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Most important content function in Knowledge Management, keyword search that provides quick response at high document relevancy
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Real Simple Syndication (RSS)
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Standard for subscribing to content sources
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Expert Systems
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attempt to capture human expertise and put it in to a system that can be used by non experts, uses rule based "if/then" statements but unlike desision trees, expert systems can have hundreds of thousands of rules (expensive and hard to maintain)
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3 major disadvantages of Expert Systems
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1. Expensive 2. Unpredictable to Maintain 3. Overhyped
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Static Reports
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BI Documents that are fixed at the time of creation and do not change
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Dynamic Reports
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BI Documents that are updated at the time they are requested
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Subscriptions
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user requests for a particular BI result on a particular schedule or in response to an event
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BI Server
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Web aplication that is purpose built for the publishing of business intelligence (Example: Microsoft SQL Server report Manager)
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2 Main Functions of a BI Server
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Management & Delievery
