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Business Analytics > Overview of Big Data and Business Analytics > Flashcards

Overview of Big Data and Business Analytics Flashcards

Prelim

1
Q

In the era of knowledge economy, what is critical to the success of business?

A

Getting the right information to decision makers at the right time

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2
Q

It is one of the most talked-about topics in the field of business and information technology.

A

Business analytics

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3
Q

It is one of the most sought-after courses in the academe.

A

Business analytics

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4
Q

It is comprised of solutions used to build analysis models and simulations to create scenarios, understand realities and predict future states.

A

Business analytics

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5
Q

It includes data mining, predictive analytics, applied analytics, and statistics.

A

Business analytics

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6
Q

Business analytics is comprised of solutions used to build analysis models and simulations to what?

(CUP)

A
  1. Create scenarios
  2. Understand realities
  3. Predict future states
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7
Q

It is the study of data through statistical and operations analysis, the formation of predictive models, application of optimization techniques, and the communication of these results to customers, business partners, and college executives.

A

Business analytics

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8
Q

Business analytics is the study of data through what?

(STAT)

A
  1. Statistical and operations analysis
  2. The formation of predictive models
  3. Application of optimization techniques
  4. The communication of these results to customers, business partners, and college executives
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9
Q

It refers to a broad use of various quantitative techniques such as statistics, data mining, optimization tools, and simulation supported by the query and reporting mechanism to assist decision makers in making more informed decisions within a closed-loop framework seeking continuous process improvement through monitoring and learning.

A

Business analytics

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10
Q

What are the various quantitative techniques used in business analytics?

(SODS)

A
  1. Statistics
  2. Optimization tools
  3. Data mining
  4. Simulation
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11
Q

It is the process of collecting information from all sources to make data-driven decisions in an organization.

A

Business Intelligence

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12
Q

It is the process of combining aspects of reporting, monitoring, and alerting, dashboards, scorecards, and ad hoc query data exploration.

A

Business Intelligence

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13
Q

Business intelligence is the process of combining aspects of what?

(SADMAR)

A
  1. Scorecards
  2. Alerting
  3. Dashboards
  4. Monitoring
  5. Ad hoc query data exploration
  6. Reporting
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14
Q

Business analytics is supported by the query and reporting mechanism to assist decision makers in making what?

A

More informed decisions

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15
Q

Who described the challenges with Business Analytics?

A

John Jordan (Penn State University)

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16
Q

What did John Jordan stated as he described the challenges with Business Analytics?

A

He stated that “a greater potential for privacy invasion, greater financial exposure in fast-moving markets, greater potential for mistaking noise for true insight, and a greater risk of spending lots of money and time chasing poorly defined problems or
opportunities.”

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17
Q

What are the challenges mentioned by John Jordan?

(PGGG)

A
  1. Potential for privacy invasion
  2. Greater financial exposure in fast-moving markets
  3. Greater potential for
    mistaking noise for true insight
  4. Greater risk of spending lots of
    money and time chasing poorly defined problems or
    opportunities
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18
Q

What are the challenges mentioned by John Jordan?

(APIECEE)

A
  1. Available Production Data vs. Cleansed Modeling Data (APD vs. CMD)
  2. Project Management Office (PMO)
  3. IT involvement
  4. Executive ownership
  5. Change management
  6. End-user Involvement and Buy-In
  7. Explainability vs the “Perfect Lift”
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19
Q

This challenge means business analytics requires buy-in from senior leadership and a clear corporate strategy for integrating predictive models.

A

Executive Ownership

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20
Q

This challenge means technology infrastructure and tools must be able to handle the data and Business Analytics processes.

A

IT involvement

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21
Q

This challenge means to watch for technology infrastructure that restricts available

A
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22
Q

This challenge means to watch for technology infrastructure that restricts available data for historical modeling, and know the difference between historical data for model development and real-time data in production.

A

Available Production Data vs. Cleansed Modeling Data

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23
Q

This challenge means that the correct project management structure must be in place in order to implement predictive models and adopt an agile approach.

A

Project Management Office (PMO)

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24
Q

This challenge means that the correct project management structure must be in place in order to implement predictive models and adopt an agile approach.

A

Project Management Office (PMO)

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25
Q

This challenge means that end-users should be involved in adopting Business Analytics and have a stake in the predictive model.

A

End-user Involvement and Buy-In

26
Q

This challenge means that organizations should be prepared for the changes that Business Analytics bring to current business and technology operations.

A

Change management

27
Q

This challenge means that organizations should be prepared for the changes that Business Analytics bring to current business and technology operations.

A

Change management

28
Q

This challenge means that balance building precise statistical models with being able to explain the model and how it will produce results.

A

Explainability vs the “Perfect Lift”

29
Q

This challenge means that balance building precise statistical models with being able to explain the model and how it will produce results.

A

Explainability vs the “Perfect Lift”

30
Q

What are the most important Best Practices for Business Analytics?

(KDSV)

A
  1. Know the objective for using Business Analytics. Define your business use case and the goal ahead of time.
  2. Define your criteria for success and failure.
  3. Select your methodology and be sure you know the data and relevant internal and external factors.
  4. Validate models using your predefined success and failure criteria.
31
Q

What are the Business Analytics Goals?

(GI³E)

A
  1. Gaining insights into business practices and customer behavior.
  2. Improving predictability.
  3. Identifying risk.
  4. Improving the effectiveness of communication.
  5. Enhancing operating efficiency.
32
Q

Which Business Analytics Goal means that Business Analytics is designed to transform unstructured, nonstandardized big data originated from multiple sources into meaningful information helpful for a better business decision?

A

Gaining insights into business practices and customer behavior.

33
Q

Which Business Analytics Goal means that by deriving insights into customer behavioral patterns and market trends, business analytics can improve the organization’s ability to make demand forecast more accurately?

A

Improving predictability.

34
Q

Which Business Analytics Goal means that risk can’t be managed without identifying it and then preparing for it?

A

Identifying risk.

35
Q

Which Business Analytics Goal means that BA can function as an early warning system for detecting the signs or symptoms of potential troubles by dissecting the business patterns?

A

Identifying risk.

36
Q

Which Business Analytics Goal means that with the query and reporting mechanism of business analytics, it can only speed up the reporting procedures, but also provide user-friendly reports including “what-if” scenarios?

A

Improving the effectiveness of communication.

37
Q

Which Business Analytics Goal means that by aiding the decision maker in understanding the way business works and where the greatest business opportunities are, BA can decrease the chances of making poor investment decisions and misallocating company resources?

A

Enhancing operating efficiency

38
Q

What is the history of business analytics?

A

• Use of sticks and stones.
• 1800s - Industrial Age; Henry Ford and the Ford Model T assembly line
• 20th century - Computers; Introduction of Decision Support System in 1970s
• 21st century - Internet, big data, and cloud

39
Q

Business Analytics focuses on what kind of analytics of the business?

A

Financial and Operational Analytics

40
Q

Business Analytics focuses on what kind of analytics of the business?

A

Financial and Operational Analytics

41
Q

It involves machine automation to analyze data.

42
Q

It involves machine automation to analyze data.

43
Q

What is the importance of big data?

A

It is not how much data is available but what to do with the data.

44
Q

It is a huge volume of structured and unstructured data that is generated everyday in the world.

45
Q

What are the four aspects that define data?

(4Vs)

A
  1. Variety
  2. Velocity
  3. Veracity
  4. Volume
46
Q

This data is so complex that it becomes almost impossible to analyze them manually or with the use of basic data management tools.

47
Q

It is the speed of data.

48
Q

It means that there are a lot of uncertainty from the data.

49
Q

It is about how huge data sets are.

50
Q

It includes how many pieces of data were gathered together.

51
Q

Data can be taken from any sources and analyze it to find answers that enable what?

A

• Cost reductions
• Time reductions
• New product development and optimize offerings
• Smart decision making

52
Q

What business-related tasks can be accomplished when big data is combined with high-powered analytics?

(DRGD)

A

Determining the root cause of failures near-real time
Recalculating entire risk portfolios
Generating coupons at POS
Detecting fraudulent behavior

53
Q

What are the 5 Key Steps to taking charge of this big “data fabric”?

(SKAAM)

A

Set a big data strategy.
Know the sources of data.
Access, manage, and store big data.
Analyze big data.
Make intelligent, data-driven decisions.

54
Q

What sets the stage for business success amid an abundance of data?

A

Big data strategy

55
Q

When developing a strategy, what kind of business and technology goals and initiatives are important to consider?

A

Existing and future

56
Q

What should the companies treat big data as?

A

As like any other valuable asset rather than just a byproduct

57
Q

It comes from the Internet of Things and other connected devices that flow into IT systems.

A

Streaming Data

58
Q

It stems from interactions on FB, YT, IG, etc.

A

Social Media

59
Q

This includes vast amounts of big data in the form of images, videos, voice, text, and sound.

A

Social Media

60
Q

It comes from massive amounts of open data sources.

A

Publicly available data

61
Q

Other big data may come from what sources?

A

Data lakes
Cloud data sources
Suppliers
Customers

Business Analytics (6 decks)

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