Chapter 15 Flashcards

1
Q

At what rate is data expanding?

A

The amount of data being created doubles every two years

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2
Q

What is one of the problems with data and how is it being solved?

A

In many organizations, available data is not exploited to advantage. However new tools supporting big data, business intelligence, and analytics are helping managers make sense of this data torrent.

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3
Q

What is data and what must be done to it to make it useful?

A

Data includes raw facts that must be turned into information in order to be useful and valuable.

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4
Q

What is a DBMS?

A

Databases are created, maintained, and manipulated using programs called database management systems (DBMS), sometimes referred to as database software.

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5
Q

What is a RDBMS?

A

Relational database management systems (RDBMS) are the most common database standard by far, and SQL (or structured query language) is the most popular standard for relational database systems.

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6
Q

Describe a relational database system? How are files linked?

A

In relational database systems, several data fields make up a data record, multiple data records make up a table or data file, and one or more tables or data files make up a database. Files that are related to one another are linked based on a common field (or fields) known as a key. If the value of a key is unique to a record in a table, and that value can never occur in that field while referring to another record in that table, then it is a primary key. If a key can occur many times over multiple records in a table but relates back to a primary key in another table, then it is a foreign key.

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7
Q

What is a TPS?

A

For organizations that sell directly to their customers, transaction processing systems (TPS) represent a source of potentially useful data.

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8
Q

Why might grocers and retailers want you to use a loyalty card?

A

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.

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9
Q

Name 3 data sources and what type of data would be found there.

A

Enterprise software (CRM, SCM, and ERP) is a source for customer, supply chain, and enterprise data.

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10
Q

Name a type of data that might supplement a firm’s operational data.

A

Survey data can be used to supplement a firm’s operational data.

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11
Q

What two types of data should be combined to give a firm a competitive edge?

A

Data obtained from outside sources, when combined with a firm’s internal data assets, can give the firm a competitive edge.

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12
Q

Why are data aggregators important?

A

Data aggregators are part of a multibillion-dollar industry that provides genuinely helpful data to a wide variety of organizations.

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13
Q

How should third party data from an aggregator be utilized?

A

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.

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14
Q

How are data aggregators controversial?

A

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.

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15
Q

What are the risks of data mismanagement?

A

Firms that mismanage their customer data assets risk lawsuits, brand damage, lower sales, fleeing customers, and can prompt more restrictive legislation.

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16
Q

What have recent studies shown that raises concerns about privacy issues and identity theft?

A

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.

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17
Q

What might be the result of privacy issues and identity theft?

A

New methods for tracking and gathering user information are raising privacy issues which possibly will be addressed through legislation that restricts data use.

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18
Q

Name a major factor limiting business intelligence initiatives?

A

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).

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19
Q

What are some problems related to legacy systems?

A

Legacy systems often limit data utilization because they were not designed to share data, aren’t compatible with newer technologies, and aren’t aligned with the firm’s current business needs.

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20
Q

What is a problem with transactional databases?

A

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.

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21
Q

What is the purpose of a data warehouse?

A

Data warehouses and data marts are repositories for large amounts of transactional data awaiting analytics and reporting.

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22
Q

What are some challenges to data warehouses?

A

Large data warehouses are complex, can cost millions, and take years to build.

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23
Q

Describe Hadoop.

A

The open source Hadoop effort provides a collection of technologies for manipulating massive amounts of unstructured data. The system is flexible, scalable, cost-effective, and fault-tolerant. Hadoop grew from large Internet firms but is now being used across industries.

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24
Q

What are 3 ways to transform data to information?

A

Canned and ad hoc reports, digital dashboards, and OLAP are all used to transform data into information.

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25
Q

Describe how OLAP reporting leverages data cubes?

A

OLAP reporting leverages 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.

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26
Q

What is a problem with modern data sets?

A

Modern data sets can be so large that it might be impossible for humans to spot underlying trends without the use of data mining tools.

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27
Q

What are three ways businesses are using data mining?

A

Businesses are using data mining to address issues in several key areas including customer segmentation, marketing and promotion targeting, collaborative filtering, and so on.

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28
Q

What are 3 ways machine learning and other types of AI are being applied?

A

Machine learning and other types of AI are being applied in all sorts of ways, including voice and image recognition, enabling self-driving cars, writing news articles and other content, and making scientific discovery.

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29
Q

What are 3 reasons models will yield bad results?

A

Models influenced by bad data, missing or incomplete historical data, and over-engineering are prone to yield bad results.

30
Q

What is one way to test to see if you’re looking at a random occurrence in your data?

A

One way to test to see if you’re looking at a random occurrence in your data is to divide your data, building your model with one portion of the data, and using another portion to verify your results.

31
Q

What is one challenge to using analytics?

A

Analytics may not always provide the total solution for a problem. Sometimes a pattern is uncovered, but determining the best choice for a response is less clear.

32
Q

What are 3 critical skills for a competent business analytics team?

A

A competent business analytics team should possess three critical skills: information technology, statistics, and business knowledge.

33
Q

Walmart has demonstrated what when it comes to data?

A

Walmart demonstrates how a physical product retailer can create and leverage a data asset to achieve world-class value chain efficiencies.

34
Q

Describe how Walmart uses data

A

Walmart uses data mining in numerous ways, from demand forecasting to predicting the number of cashiers needed at a store at a particular time.

35
Q

Why does Walmart share data with suppliers?

A

To help suppliers become more efficient, and as a result lower prices, Walmart shares data with them.

36
Q

What are some of the downsides to “being” Walmart?

A

Despite its success, Walmart is a mature business that needs to find huge markets or dramatic cost savings in order to boost profits and continue to move its stock price higher. The firm’s success also makes it a high impact target for criticism and activism. And the firm’s data assets could not predict impactful industry trends such as the rise of Target and other upscale discounters.

37
Q

OLAP

A

online analytical processing (OLAP)

A method of querying and reporting that takes data from standard relational databases, calculates and summarizes the data, and then stores the data in a special database called a data cube.

38
Q

data mart

A

data mart

A database or databases focused on addressing the concerns of a specific problem (e.g., increasing customer retention, improving product quality) or business unit (e.g., marketing, engineering).

39
Q

data cube

A

data cube

A special database used to store data in OLAP reporting.

40
Q

inventory turnover ratio

A

inventory turnover ratio

The ratio of a company’s annual sales to its inventory.

41
Q

SQL

A

structured query language (SQL)

A language used to create and manipulate databases.

42
Q

loyalty card

A

loyalty card

Systems that provide rewards and usage incentives, typically in exchange for a method that provides a more detailed tracking and recording of customer activity. In addition to enhancing data collection, loyalty cards can represent a significant switching cost.

43
Q

dashboards

A

dashboards

A heads-up display of critical indicators that allow managers to get a graphical glance at key performance metrics.

44
Q

legacy system

A

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.

45
Q

Genetic algorithms

A

Genetic algorithms

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.

46
Q

data mining

A

data mining

The process of using computers to identify hidden patterns in, and to build models from, large data sets.

47
Q

omnichannel

A

omnichannel

Providing customers with a unified experience across customer channels, which may include online, mobile, catalog, phone, and retail. Pricing, recommendations, and incentives should reflect a data-driven, accurate, single view of the customer

48
Q

neural networks

A

neural networks

An AI system that examines data and hunts down and exposes patterns, in order to build models to exploit findings.

49
Q

information

A

information

Data presented in a context so that it can answer a question or support decision making.

50
Q

knowledge

A

knowledge

Insight derived from experience and expertise

51
Q

big data

A

big data

Big data is a general term used to describe the 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.

52
Q

analytics

A

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.

53
Q

canned reports

A

canned reports

Reports that provide regular summaries of information in a predetermined format.

54
Q

row or record

A

row or record

A row in a database table. Records represent a single instance of whatever the table keeps track of (e.g., student, faculty, course title).

55
Q

column or field

A

column or field

A column 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).

56
Q

Expert systems

A

Expert systems

AI systems that leverage rules or examples to perform a task in a way that mimics applied human expertise.

57
Q

table or file

A

table or file

A list of data, arranged in columns (fields) and rows (records).

58
Q

relational database

A

relational database

The most common standard for expressing databases, whereby tables (files) are related based on common keys.

59
Q

artificial intelligence

A

artificial intelligence

Computer software that seeks to reproduce or mimic (perhaps with improvements) human thought, decision making, or brain functions.

60
Q

e-discovery

A

e-discovery

The process of identifying and retrieving relevant electronic information to support litigation efforts

61
Q

BI

A

business intelligence (BI)

A term combining aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis.

62
Q

data warehouse

A

data warehouse

A set of databases designed to support decision making in an organization.

63
Q

TPS

A

transaction processing systems (TPS)

Systems that record a transaction (some form of business-related exchange), such as a cash register sale, ATM withdrawal, or product return.

64
Q

data

A

data

Raw facts and figures.

65
Q

transaction

A

transaction

Some kind of business exchange.

66
Q

database

A

database

A single table or a collection of related tables.

67
Q

machine learning

A

machine learning

Leverages massive amounts of data so that computers can act and improve on their own without additional programming.

68
Q

DBA

A

database administrator (DBA)

Job title focused on directing, performing, or overseeing activities associated with a database or set of databases. These may include (but not necessarily be limited to): database design, creation, implementation, maintenance, backup and recovery, policy setting and enforcement, and security.

69
Q

data aggregators

A

data aggregators

Firms that collect and resell data.

70
Q

ad hoc reporting tools

A

ad hoc reporting tools

Tools that put users in control so that they can create custom reports on an as-needed basis by selecting fields, ranges, summary conditions, and other parameters.

71
Q

over-engineer

A

over-engineer

Build a model with so many variables that the solution arrived at might only work on the subset of data you’ve used to create it.

72
Q

DBMS

A

database management systems (DBMS)

Sometimes called “database software”; software for creating, maintaining, and manipulating data.