CHAPTER 6 notes fro the exam 2.docx

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Department
Operations & Info Management
Course
OIM 210
Professor
Ryan Wright
Semester
Fall

Description
CHAPTER 6  big data-Ageneral term used to describe massive amount of data available to today’s managers. Big data are often unstructured and are too big and costly to easily work through use of conventional databases, but new tools are making these massive datasets available for analysis and insight.  business intelligence (BI) -Aterm combining aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis.  Analytics Aterm 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.Alone it tells you nothing. The real goal is to turn data into information. Data becomes information when it’s presented in a context so that it can answer a question or support decision making.And it’s when this information can be combined with a manager’s knowledge—their insight from experience and expertise—that stronger decisions can be made.  Database -Asingle table or a collection of related tables. Various databases might be focused on any combination of functional areas (sales, product returns, inventory, payroll), geographical regions, or business units. Firms often create specialized databases for recording transactions, as well as databases that aggregate data from multiple sources in order to support reporting and analysis.  database management systems (DBMS)- Sometimes called “databade software”; software for creating, maintaining, and manipulating data.  structured query language (SQL)- relational database; by far the most common language for creating and manipulating databases. You’ll find variants of SQL inhabiting everything from lowly desktop software, to high-powered enterprise products.  Column/field -Acolumn in a database table. Columns represent each category of data contained in a record (e.g., first name, last name, ID number, date of birth)  Key - Code that unlocks encryption.  table or file -Alist of data, arranged in columns (fields) and rows (records)  database administrator (DBA) - Job title focused on directing, performing, or overseeing activities associated with a database or set of databases. These may include: database design, creation, implementation, maintenance, backup and recovery, policy setting and enforcement, and security  relational database -The most common standard for expressing databases, whereby tables (files) are related based on common keys.  transaction processing systems (TPS) -Systems that record a transaction such as a cash register sale,ATM withdrawal, or product return.  For organizations that sell directly to their customers, transaction processing systems (TPS) represent a source of potentially useful data.  Grocers and retailers can link you to cash transactions if they can convince you to use a loyalty card which, in turn, requires you to give up information about yourself in exchange for some kind of financial incentive such as points or discounts.  Enterprise software (CRM, SCM, and ERP) is a source for customer, supply chain, and enterprise 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.  legacy system -Older information systems that are often incompatible with other systems, technologies, and ways of conducting business. Incompatible legacy systems can be a major roadblock to turning data into information, and they can inhibit firm agility, holding back operational and strategic initiatives.  Amajor 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
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