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The most common feeds into BI Systems are:
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Operational databases
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Social Data
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Purchased data
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Employee Knowledge
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The four main uses of BI are:
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Project management
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Problem solving
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Deciding
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Informing
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An example of using BI for project management is [blank_start]the creation of Gear UP[blank_end]
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the creation of Gear UP
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determining ways to reduce costs
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determining # of soccer balls to sell
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comparing sales to forecast
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An example of how to use BI for problem solving is [blank_start]creating Gear Up[blank_end]
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creating Gear Up
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determining how to reduce costs
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finding out # soccer balls can we sell
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comparing sales to forecast
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An example of using BI for making decisions is [blank_start]creating Gear up[blank_end]
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creating Gear up
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determining how to reduce costs
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finding out # soccer balls to sell
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comparing sales to forecast
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An example of using BI to inform is [blank_start]creating Gear up[blank_end]
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creating Gear up
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determining how to reduce costs
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finding out # soccer balls to sell
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comparing sales to forecast
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Typical uses for BI are
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identifying changes in purchasing patterns
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keeping track of people's reading, watching and listening habits
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predictive policing
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The three primary activities in the BI process are
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Acquiring data
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Performing analysis
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Publishing results
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The acquiring data activity also includes
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cleansing
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organizing and relating
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cataloging
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The analysis activity includes
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data mining
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knowledge management
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Results may be published by
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printing and distributing via email or a collaboration tool
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publish on a web server or via SharePoint
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publish on a BI server
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automate results via a web service
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Pushing information means automatically sending it to users
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Pulling information means that the user must make a request for it
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As long as two tables have a field in common, then the tables can be joined.
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A data broker is also known as a data miner.
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Data brokers gather data from
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public records
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retailers
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internet cookie vendors
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social medial trackers
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others
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Data brokers gather this data to create business intelligence that they then sell to organizations and the government.
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Cloud processing has made processing consumer data cheaper and faster.
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It is easy to request and make sense of data that has been gathered about yourself.
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Cleansing data means scanning it for viruses.
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BI analysis is performed on the same servers that run the operations of the organization.
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The DBMS of a data warehouse consists of
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Data warehouse metadata
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Data warehouse database
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From a data warehouse can be created one or several data marts
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Examples of BI tools that can be used for specific data marts are
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In the US, it is not difficult for an aggregator to purchase information including an individual's name, address, phone number, income, marital status, name(s) of spouse and children, etc.
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Source data can be too granular or not granular enough.
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the basic operations of reporting applications are
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Sorting
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Filtering
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Grouping
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Calculating
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Formating
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The acronym RFM stands for [blank_start]Recently, Frequently, and Money[blank_end].
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Unsupervised data mining refers to data mining performed by an inexperienced analyst.
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Cluster analysis is an example of unsupervised data mining
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Supervised data mining uses an a priori model to compute the outcome of that model.
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Market-basket analysis consists of
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identifying sales patterns in large volumes of data
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identifying products that customers tend to purchase together
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probabilities of customer purchases
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identification of cross-selling opportunities
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Decision trees are a supervised data mining technique.
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Big Data applications can only be used with structured data.
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The storage part of Hadoop is called the HDFS - Hadoop Distributed File System.
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The processing part of Hadoop is called MapReduce.
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The goal of Knowledge Management is to use the organization's collective knowledge to improve process quality and team strength.
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Knowledge management creates [blank_start]value from intellectual capital[blank_end] and allows for the sharing of knowledge with those that need that capital.
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Expert systems are created by [blank_start]gathering knowledge from human experts.[blank_end]
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Expert systems are cheap and easy to develop.
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Expert systems are difficult to maintain.
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Expert systems often disappoint because they can't duplicate the diagnostic abilities of humans.
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CMS stands for [blank_start]Content Management System[blank_end].
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Some of the challenges of content management systems include
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An organization can provide content management by
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The main functions of a data warehouse are