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FBA > FBA GROUP 1, 2 AND 3 > Flashcards

FBA GROUP 1, 2 AND 3 Flashcards

1
Q

business analytics involves identifying and assessing all aspects of a decision, and taking actions based on the decision that produces the most favorable outcome.

A

DECISION MAKING

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2
Q

It uses facts and data instead of guesses to make better
decisions. It helps find trends, improve processes, and reach business goals while reducing risks.

A

The Importance of Data-driven decision- making

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3
Q

According to _________ prescriptive analytics focuses on recommending actions to achieve
desired outcomes based on data analysis.

A

James R. Evans

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4
Q
  • It goes beyond descriptive and predictive analytics by providing specific guidance on what decisions or
    strategies to implement, often using optimization and simulation techniques.
  • This type of analytics helps organizations determine the best course of action to improve performance
    and meet objectives.
A

PRESCRIPTIVE ANALYTICS

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5
Q

ROLE OF PRESCRIPTIVE ANALYTICS IN DECISION MAKING

A
  • Optimizing Choices
  • Navigating Uncertainty
  • Enhancing Speed
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6
Q

PRESCRIPTIVE ANALYTICS’ CORE COMPONENTS

A

PREDICTIVE MODELS
DATA
OPTIMIZATION TOOLS

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7
Q

TOOLS AND TECHNIQUES

A
  • OPTIMIZATION MODELS
  • SIMULATION
  • DECISION ANALYSIS
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8
Q

APPLICATIONS OF PRESCRIPTIVE ANALYTICS

A

SUPPLY CHAIN
FINANCE
HEALTHCARE
MARKETING

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9
Q

STEPS IN THE DECISION- MAKING PROCESS

A
  1. Define the problem and objectives.
  2. Develop the prescriptive model.
  3. Analyze potential solutions.
  4. Evaluate trade-offs and risks.
  5. Implement the optimal solution.
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10
Q

BENEFITS OF PRESCRIPTIVE ANALYTICS

A
  • Data-driven decisions enhance accuracy.
  • Mitigates risk and uncertainty.
  • Optimizes resource allocation and operations.
  • Improves financial and strategic outcomes.
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11
Q

CHALLENGES IN IMPLEMENTATION

A
  • Data quality and availability issues.
  • High computational complexity.
  • Need for domain expertise and advanced tools.
  • Integration with existing systems and workflows.
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12
Q

Forecast trends and possibilities.

A

PREDICTIVE MODELS

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13
Q

Transactional, Customer, Operational, Financial

A

DATA

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14
Q

Generate actionable recommendations.

A

OPTIMIZATION TOOLS

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15
Q

are mathematical frameworks used to find the best possible solution from a set of available alternatives, subject to certain constraints.

A

OPTIMIZATION MODELS

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16
Q

Is a technique used to imitate the operation of a real-world process or system over time.

A

SIMULATION

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17
Q

a systematic, quantitative, and visual approach to making complex decisions It involves identifying and evaluating various options by considering the possible outcomes, uncertainties,
and trade-offs.

A

DECISION ANALYSIS

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18
Q

Prescriptive analytics helps optimize logistics, manage inventory, and improve efficiency by recommending the best actions based on data.

A

SUPPLY CHAIN

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19
Q

it is used for making better investment decisions, managing risks, and detecting fraud by analyzing data and suggesting optimal strategies.

A

FINANCE

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20
Q

It improves patient care, resource management, and cost efficiency by recommending the best treatment plans and operational actions.

A

HEALTHCARE

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21
Q

Prescriptive analytics helps create effective marketing campaigns, personalize customer
experiences, and allocate budgets by analyzing consumer data.

A

MARKETING

22
Q

What is Big Data?

A

Beyond Traditional Data
A Growing Trend

23
Q

refers to datasets that are too large and complex to be managed by traditional methods. They often
come from various sources like social media, sensors, and transactions.

A

Big Data

24
Q

The amount of data generated worldwide is growing at an exponential rate. This volume and complexity
require new approaches to analysis and storage.

A

A Growing Trend

25
Q

Characteristics of Big Data

A

Volume
Variety
Velocity
Veracity
Value

26
Q

Vast amount of data generated daily.

A

Volume

27
Q

Data come in diverse formats, including structured, semi structured, and unstructured data.

A

Variety

28
Q

Data is generated rapidly, requiring real-time processing and analysis.

A

Velocity

29
Q

Data quality is crucial for accurate insights. Refers to the reliability and trust worthiness
of data

A

Veracity

30
Q

Extracting meaningful insights from data.

A

Value

31
Q

The Need for Big Data

A

*Better Decisions:
*New Opportunities:
*Personalized Experiences:

32
Q

Challenges with Traditional Data Management

A

Scalability
Speed
Complexity

33
Q

Traditional databases struggle to handle and the massive scale and complexity of Big Data, leading to
performance bottlenecks and storage limitations.

A

Scalability

34
Q

Traditional system often lack the speed and agility required to process Big Data in real-time, making it difficult
to extract actionable insights quickly.

A

Speed

35
Q

Analyzing diverse and unstructured data requires specialized tools and techniques that traditional system
may not offer.

A

Complexity

36
Q

Introducing Data Warehouse

A

Centralized Storage
Data Integration
Analytical Powerhouse

37
Q

A data warehouse is a central repository for sorting and managing vast amounts of data from various sources

A

Centralized Storage

38
Q

It integrates data from different systems into a consistent format, enabling comprehensive analysis.

A

Data Integration

39
Q

It provides a platform for performing complex data analysis and generating valuable insights.

A

Analytical Powerhouse

40
Q

Key Components of Data Warehouse

A

Data Sources
ETL Processes
Data Marts

41
Q

Various sources, such as databases, log files, social media, and sensors, provide data for the
warehouse.

A

Data Sources

42
Q

Extract, Transform, Load clean, transform, and load data into the warehouse.

A

ETL Processes

43
Q

Smaller, specialized datasets are extracted from the warehouse to support specific business needs.

A

Data Marts

44
Q

Benefits of a Data Warehouse

A

Improve Insights
Better Decisions
Enhanced Efficiency

45
Q

Comprehensive data analysis leads to better understanding of customer behavior, market trends, and
operational performance

A

Improve Insights

46
Q

Data-driven insights enable organizations to make informed decisions across various departments and
functions

A

Better Decisions

47
Q

Optimized resource allocation, improved customer service, and streamlined operations lead to increased
efficiency.

A

Enhanced Efficiency

48
Q

Big Data enables businesses to make better, data-driven decisions, leading to improved efficiency,
productivity, and customer satisfaction.

A

Better Decisions

49
Q

By analyzing large datasets, organizations can identify new trends, market opportunities, and potential risks,
driving innovation and growth.

A

New Opportunities

50
Q

Big Data fuels personalization in various industries. It allows businesses to tailor products, services, and
marketing campaigns to individual preferences.

A

Personalized Experiences

FBA (3 decks)

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