Notes for Exam 1 11 29 2012 CHAPTER 11 The Data Asset Databases Business Intelligence and Competitive Advantage Business Intelligence a catchall term combining aspects of reporting data exploration and ad hoc queries and sophisticated data modeling and analysis Analytics a term describing the extensive use of data statistical and quantitative analysis explanatory and predictive models and fact based management to drive decisions and actions The amount of data on corporate hard drives doubles every six months In many organizations available data is not exploited to advantage Data is oftentimes considered a defensible source of competitive advantage however advantages based on capabilities and data that others can acquire will be short lived Data refers simply to raw facts and figures Information data becomes information when it s presented in a context so that it can answer a question or support decision making knowledge their insight from experience and expertise Database single table or collection of related tables Database management systems database software software for creating maintaining and manipulating data Structured query language SQL the most common language for creating and manipulating databases Database administrator directing performing and overseeing activities related to a database Table or file list of data Column or field defines data a table can hold Row or record single instance of whatever the table keeps track of Key field used to relate tables in a database Rational databases the most common standard for expressing databases where tables are related based on common keys Transaction processing systems TPS systems that record a transaction some kind of business exchange such as cash register sale ATM withdrawal or product return Loyalty card systems that provide rewards and usage incentives provides a more detailed tracking of customer activity Enterprise software CRM SCM and ERP is a source for customer supply chain and enterprise data Survey data can be used to supplement a firm s operational data Data obtained from outside sources when combined with a firm s internal data assets can give the firm a competitive edge Data aggregators are part of a multibillion dollar industry that provides genuinely helpful data to a wide variety of organizations Data that can be purchased from aggregators may not in and of itself yield sustainable competitive advantage since others may have access to this data too However when combined with a firm s proprietary data or integrated with a firm s proprietary procedures or other assets third party data can be a key tool for enhancing organizational performance Data aggregators can also be quite controversial Among other things they represent a big target for identity thieves are a method for spreading potentially incorrect data and raise privacy concerns Firms that mismanage their customer data assets risk lawsuits brand damage lower sales fleeing customers and can prompt more restrictive legislation Further raising privacy issues and identity theft concerns recent studies have shown that in many cases it is possible to pinpoint users through allegedly anonymous data and to guess Social Security numbers from public data New methods for tracking and gathering user information are raising privacy issues which possibly will be addressed through legislation that restricts data use legacy systems outdated information systems that were not designed to share data aren t compatible with newer technologies and aren t aligned with the firm s current business needs A major factor limiting business intelligence initiatives is getting data into a form where it can be used i e analyzed and turned into information Most transactional databases aren t set up to be simultaneously accessed for reporting and analysis In order to run analytics the data must first be ported to a data warehouse or data mart Data warehouse a set of databases designed to support decision making in an organization Data mart a database focused on addressing the concerns of a specific problem e g increasing customer retention improving product quality or business unit e g marketing engineering E discovery refers to identifying and retrieving relevant electronic information to support litigation efforts Data warehouses and data marts are repositories for large amounts of transactional data awaiting analytics and reporting Large data warehouses are complex can cost millions and take years to build Canned reports provide regular summaries of information in a predetermined format they re often developed by information systems staff and formats can be difficult to alter ad hoc reporting tools allow users to dive in and create their own reports selecting fields ranges and other parameters to build their own reports on the fly Dashboards provide a sort of heads up display of critical indicators letting managers get a graphical glance at key performance metrics A subcategory of reporting tools is referred to as Online analytical processing OLAP pronounced oh lap a subcategory of reporting tools data used in OLAP reporting is usually sourced from standard relational databases but it s calculated and summarized in advance across multiple dimensions with the data stored in a special database called data cube Data mining the process of using computers to identify hidden patterns and to build models from large data sets over engineer a model building it with so many variables that the solution arrived at might only work on the subset of data you ve used to create it Neural networks an artificial intelligence system Ai that examines data hunts down and exposes patterns in order to build models to exploit findings Expert systems are AI systems that leverage rules or examples to perform a task in a way that mimics applied human expertise Genetic algorithms are model building techniques where computers examine many potential solutions to a problem iteratively modifying mutating various mathematical models and comparing the mutated models to search for a best alternative Canned and ad hoc reports digital dashboards and OLAP are all used to transform data into information OLAP reporting leverage data cubes which take data from standard relational databases calculating and summarizing data for superfast reporting access OLAP tools can present results through multidimensional graphs or via spreadsheet style cross tab reports Modern data sets can be so large that it might be impossible for
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