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MIS Exam #2 > Decision Making & Knowledge Management > Flashcards

Decision Making & Knowledge Management Flashcards

1
Q

What process do decision makers follow?

A

A repeatable process

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2
Q

Steps in the Decision Process

A
  1. Define the problem
  2. Identify limiting factors
  3. Develop potential alternatives
  4. Analyze the alternatives
  5. Select the best alternative
  6. Implement the decision
  7. Establish a control and evaluation system
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3
Q

Structured Data

A
  • Everything so far in course
  • ERD
  • Organizational Databases
  • ERP
  • Clearly defined data entities, types, relationships, hierarchies
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4
Q

Unstructured Data

A
  • User generated data
  • Email
  • Tweets
  • Comments
  • Images
  • Videos
  • Blogs
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5
Q

Types of Decisions You Face

A

Recurring/Non-recurring

Unstructured/Structured

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6
Q

What type of decision is your daily/weekly regimented tasks?

A

Structured & Recurring

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7
Q

What type of decision is using analytics to solve complex problems and questions?

A

Unstructured & Non-recurring

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8
Q

Analytics

A

The process of making sense of large data sets and unlocking patterns, often using data visualization, to enable better decision making

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9
Q

Data Analytics

A

Art/Science of examining raw data for the purpose of gaining insight and drawing actionable conclusions about business problems

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10
Q

Big Data Analytics

A

Process of examining big data to uncover hidden patterns, unknown correlations, and other useful information that can be used to make better decisions

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11
Q

What should we do with all of this data?

A

Data –> Information –> Knowledge

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12
Q

Descriptive Analytics

A
  • Tracks consumer behavior
  • Describes what is happening
  • “How do users interface with a website?”
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13
Q

Predictive Analytics

A
  • What will consumers buy?

- When will demand surge?

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14
Q

Why should you care about data?

A
  • Cost reduction
  • Faster, better decision making
  • New products and services
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15
Q

What does Google Analytics track?

A
  • Site metadata/user engagement
  • # of sessions
  • Average session duration
  • Number of pages visited and duration at each
  • Bounce rate
  • Conversion
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16
Q

Why do some organizations resist data driven decision making?

A

Because they don’t like what the data is telling them; People don’t like to be held accountable for problems

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17
Q

OTLP (Online Transaction Processing)

A

Class of information systems that facilitate and manage transaction-oriented applications, typically for data entry and retrieval transaction processing

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18
Q

OLAP (Online Analytical Processing)

A

Computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than 3

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19
Q

Characterization of OLTP vs. OLAP

A
  • OLTP: large number of short on-line transactions

- OLAP: relatively low volume of transactions

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20
Q

Hypercube

A

Multi-dimensional “cubes” of information that summarize transactional data across a variety of dimensions

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21
Q

Knowledge Management

A
  • Process of capturing, developing, sharing, and effectively using organizationalknowledge
  • Refers to a multi-disciplinary approach to achieving organizational objectives by making the best use ofknowledge
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22
Q

Why are CEOs worried about Baby Boomers?

A

Because they are starting to retire so they will be losing out on these essential skills

23
Q

What are communities of practice composed of?

A

Domain
Community
Practice
Purpose

24
Q

Examples of Business Constraints

A

Budget, Schedule, Scope, Time

25
Q

Satisfice

A

To make the best decision possible with all the information, time, and resources available

26
Q

Nominal Group Technique

A
  • Highly structured meeting/agenda
  • Restricts discussion during decision making process
  • Ensures equal input
  • Avoids conformity
27
Q

Delphi Technique

A
  • Participants never meet

- Written questionnaires to conduct decision making

28
Q

How are sport franchises like small businesses?

A
  • Think they are too small to benefit from big data

- Data shows different states then what people actually think

29
Q

What did SAP do to change the world of sports?

A

Integrated a software for a drafting application that measures more meaningful and desirable traits

30
Q

Why do people tend to resist analytics?

A
  • Creates new accountability which makes people nervous
  • More data = more responsible for inefficiencies
  • More invested in acquiring analytic capabilities than confronting accountability crisis
31
Q

What are the assets of Knowledge Managements?

A

-Databases, documents, policies, procedures, expertise

32
Q

Explicit Knowledge

A

Information or knowledge that is set in tangible form

33
Q

Implicit Knowledge

A

Information or knowledge that is not set in tangible form but could be made explicit

34
Q

Tacit Knowledge

A

Information or knowledge that one would have extreme difficulty operationally setting out in tangible form

35
Q

Lesson Learned Database

A

Databases that attempt to capture and to make accessible knowledge that has been operationally obtained and typically wouldn’t be captured in fixed medium

36
Q

Community of Practice

A
  • Groups of individuals with shared interests that come together in person or virtually to tell stories, share/discuss problems/opportunities, talk about lessons learned, etc.
  • Ex: World Bank
37
Q

KM Development Stages

A
    1. Driven by IT
    1. HR/Corporate Culture
    1. Taxonomy and Content Management
38
Q

Data Analytics

A

The use of tools and people to uncover hidden patterns in data that might not be readily available to the naked eye

39
Q

Google Analytics

A

-Tracks web site metadata and user engagement

40
Q

What is OTLP composed of?

A

High Transaction Volume + Quick Data Entry/Retrieval + Data Integrity

41
Q

What is OLAP composed of?

A

Complex Queries + Data Mining + Multi Dimensional Reporting

42
Q

What is the focus difference between OLAP and OLTP?

A
  • OLTP focuses on business processes such as operations, business strategy, and master data transactions
  • OLAP focuses on business data warehouse with information and data mining analytics decision making
43
Q

OTLP/OLAP Database and Data Warehouse

A

-OLTP Database information is dumped into OLAP Data Warehouse (business intelligence)

44
Q

What does a Hypercube allow us to do?

A

Allows department to figure out sales at a certain time, territory, etc. by eliminating queries

45
Q

Data Marts

A
  • Chunks/smaller versions of a hypercube

- Merchandising, Advertising, Distribution, Sales, Marketing

46
Q

The Four Vs of Big Data

A
  • Volume (lots of data)
  • Variety (lots of types of data)
  • Velocity (data must be changing rapidly)
  • Veracity (truthful)
  • Ex: Weather Channel
47
Q

Big Data Tools

A
  • Storage: Hadoop
  • Processing: Hadoop Map Reduce
  • Analytics/Visualization: Tableau
48
Q

Brain Drain

A

Anticipated loss of technical skill, historical knowledge, and ability over time due to this rapid rate of retirement

49
Q

Tacit Knowledge

A
  • Difficult to transfer to others, visualize, write down
  • Gained/Learned through experience
  • Action-Oriented “how we know” information
  • Ex: How to ride a bike, learning a language, team management
50
Q

Explicit Knowledge

A
  • Academic
  • What you know
  • Easy to describe in language and transfer between people
  • Anything documented
  • Work flow, SLD, Payroll
51
Q

How do organizations transfer tacit knowledge to explicit knowledge?

A

Communities of Practice

52
Q

Benefits of KM

A
  • Improves performance
  • Decreases learning curve
  • Respond more rapidly
  • Reduces rework, share knowledge for new ideas
53
Q

Challenges of KM

A
  • Employee buy in
  • Knowledge overload
  • Keeping data accurate
54
Q

Communities of Practice

A
  • Community: creates environment for people to discuss topic
  • Domain: focuses on specific knowledge (expert)
  • Purpose: hear about everyones experiences and share own
  • Practice: continue to talk about techniques

MIS Exam #2 (4 decks)

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