SECTION 3: Defining Values for Success Flashcards

1
Q

What is the foundation of decision-making in organizations?

A

Data is the foundation of decision-making

Data-driven insights are crucial for organizational success.

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2
Q

What must organizations have to succeed alongside data?

A

A clear set of values

Values guide decision-making and ensure alignment with mission and goals.

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3
Q

What is the role of data analytics in decision-making?

A

Data analytics helps organizations make more informed decisions that align with their core values.

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4
Q

What are the practical applications of data analytics discussed?

A

Case studies and real-world examples of value-driven data analytics efforts.

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5
Q

What is necessary for building a data-driven organization?

A

Using data analytics techniques to define values for success.

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6
Q

What do clearly defined values provide for data analytics?

A

A framework for decision-making

They help drive organizational change and improvement.

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7
Q

What is a business question?

A

An inquiry that arises from a business need or problem requiring data analysis.

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8
Q

What are the types of analytics questions you will learn to answer?

A
  • Descriptive analytics question
  • Diagnostic analytics question
  • Predictive analytics question
  • Prescriptive analytics question
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9
Q

What does descriptive analytics help organizations understand?

A

Historical trends and patterns in data.

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10
Q

What is an example of a descriptive analytics question?

A

What was the average sales revenue per month for the last year?

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11
Q

What is the purpose of diagnostic analytics?

A

To identify the root cause of a problem.

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12
Q

What is a key technique used in predictive analytics?

A

Predictive modeling.

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13
Q

What does prescriptive analytics identify?

A

The best course of action in a given situation.

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14
Q

What type of analytics examines patterns and trends to understand underlying causes?

A

Exploratory analytics.

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15
Q

Fill in the blank: The Endothon Company uses _______ to forecast future demand.

A

predictive analytics.

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16
Q

What is the first step in answering prescriptive analytics questions?

A

Collect and analyze historical and current data.

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17
Q

What do organizations need to ensure about their data?

A

It remains relevant and current.

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18
Q

What is one method for collecting data?

A
  • Surveys
  • Interviews
  • Focus groups
  • Web scraping
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19
Q

What is a benefit of exploratory analytics?

A

It can help identify data errors and inconsistencies.

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20
Q

What type of analysis helps identify customer segments?

A

Customer segmentation analysis.

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21
Q

True or False: Predictive analytics can help with fraud detection.

A

True.

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22
Q

What must organizations consider when selecting data collection methods?

A

The type of data needed, sample size, and level of detail required.

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23
Q

What can diagnostic analytics reveal about product quality issues?

A

The root cause of the quality problem.

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24
Q

What is an example of a prescriptive analytics application?

A

Supply chain optimization.

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25
Q

What do data analysts help businesses understand through descriptive analytics?

A

Past performance and trends.

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26
Q

What is market research?

A

Collects and analyzes information about a market, including its size, trends, competitors, and customer preferences.

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27
Q

What are primary data collection methods used in businesses?

A

Focus groups, interviews, case studies, experiments, and observations.

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28
Q

What is web scraping?

A

The process of extracting data from websites using automated software tools.

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29
Q

What factors must organizations consider when selecting data collection methods?

A

Research objectives, budget, and timeline.

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30
Q

What are the unique characteristics of different data sources?

A

Databases, websites, and surveys.

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31
Q

What is the first data source typically used by businesses?

A

An organization’s internal database.

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32
Q

What can web analytics tools track?

A

Website visitors’ behaviors, including pages visited and demographic characteristics.

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33
Q

What are some common biases in survey data?

A

Inaccurate survey design, unrepresentative respondents, and inadequate sample size.

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34
Q

What does data quality refer to?

A

The degree to which data is accurate, complete, timely, and relevant.

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35
Q

What types of data are included in data quality requirements?

A
  • Numeric data
  • Categorical data
  • Textual data
  • Time-series data
  • Spatial data
  • Binary data
  • Multimedia data
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36
Q

What are the consequences of poor data quality?

A

Erroneous conclusions and negative impacts on business decision-making.

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37
Q

What is the purpose of data quality checks?

A

To ensure data accuracy, completeness, and reliability throughout a project.

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38
Q

What is data governance?

A

The process of ensuring that data complies with an organization’s security, privacy, and ethical policies.

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39
Q

True or False: Data sources can be both internal and external.

A

True.

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40
Q

What is customer segmentation?

A

Divides customers into different groups based on similar characteristics.

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41
Q

What is regression analysis?

A

A statistical method identifying the relationship between a dependent variable and one or more independent variables.

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42
Q

What is a decision tree?

A

A tree-like structure that distills a complex decision into simpler decisions or actions.

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43
Q

What is clustering in data analytics?

A

A technique that groups similar objects or data points based on characteristics.

44
Q

What do association rules identify?

A

Patterns and relationships between products or services.

45
Q

What is machine learning?

A

Techniques that extract insights and patterns from large datasets.

46
Q

What is time-series analysis used for?

A

To analyze historical data and forecast future trends.

47
Q

What does market basket analysis do?

A

Identifies patterns in customer purchasing behavior.

48
Q

What is process mining?

A

Analyzes and improves business processes by extracting data from various sources.

49
Q

What does a t-test compare?

A

The means of two independent samples.

50
Q

What does correlation analysis measure?

A

The degree of association or relationship between two or more variables.

51
Q

What type of data does text mining analyze?

A

Unstructured text, such as social media posts or customer reviews.

52
Q

What are neural networks designed to do?

A

Recognize patterns and relationships in data.

53
Q

What is the impact of data analytics on decision-making processes?

A

Allows decisions to be based on objective data rather than intuition.

54
Q

What is the impact of data analytics on organizational culture?

A

Promotes a culture of continuous improvement and data-driven decision-making.

55
Q

List some commonly used data analytics techniques.

A
  • Regression analysis
  • Decision trees
  • Clustering
  • Association rules
  • Machine learning
  • Time series
  • Market basket
  • Process mining
  • T-test
  • Correlation analysis
  • Text mining
  • Neural networks
56
Q

What is a neural network?

A

A model for neural networks using layers of interconnected nodes or neurons to process information and make predictions.

57
Q

What is required for businesses to effectively use neural networks?

A

Large amounts of data that can accurately train the model.

58
Q

What can data analytics provide for businesses?

A

Valuable insights that drive growth and success in various industries.

59
Q

What are the impacts of different data analytics techniques?

A

They can affect business outcomes such as revenue, customer satisfaction, or cost reduction.

60
Q

What can effective data analytics strategies improve?

A
  • Decision-making
  • Opportunities for growth and innovation
  • Operational efficiency
  • Customer satisfaction
  • Competitive advantage
61
Q

What factors determine the impact of data analytics strategies?

A

The organization’s specific goals and objectives, and how well processes and culture implement and integrate the analytics strategies.

62
Q

What is regression analysis used for in a business context?

A

To identify the most influential factors driving sales.

63
Q

How can machine learning techniques be applied in healthcare?

A

To identify patients at high risk of readmission to the hospital.

64
Q

What is clustering used for in marketing?

A

To group customers based on shared characteristics for targeted marketing strategies.

65
Q

What steps should data analysts follow to select an appropriate analysis method?

A
  • Identify the type of data present
  • Determine the research question
  • Determine the level of measurement
66
Q

What is continuous data?

A

Data that can take any numerical value within a range, such as weight, height, temperature, and time.

67
Q

What is the role of data visualization in analytics?

A

To communicate insights effectively and drive action.

68
Q

What factors influence the choice of visualization technique?

A
  • The audience
  • The message
  • The insights
69
Q

What is a line chart used for?

A

To show the trend of stock prices over time.

70
Q

What does a scatterplot analyze?

A

The relationship between two variables.

71
Q

What is a heat map used for?

A

To visualize customer behavior on a website or app.

72
Q

What is the purpose of selecting the correct metrics in data analytics?

A

To measure and evaluate a business initiative’s success.

73
Q

What can happen if metrics are tracked too frequently?

A

Noise in the data, making it difficult to identify meaningful trends.

74
Q

What is the conversion rate?

A

The percentage of website visitors who complete a desired action.

75
Q

Define churn rate.

A

The percentage of customers who stop doing business with a company over a certain period.

76
Q

What is customer lifetime value (CLV)?

A

The total value of a customer to a business throughout their relationship.

77
Q

What is return on investment (ROI)?

A

A metric that measures the profitability of an investment.

78
Q

What is predictive analytics?

A

Uses statistical algorithms and machine learning techniques to analyze historical data and predict future events.

79
Q

What was the main challenge faced by Alliah Company?

A

Generating revenue from digital and social media channels.

80
Q

What did Alliah Company need to do to succeed in digital media?

A

Employ cutting-edge analytics tools to ask the right business questions.

81
Q

What demographic characterized the audience with high engagement rates on social media?

A

Younger individuals with an interest in ‘soft content.’

82
Q

What was the outcome of Alliah Company’s analytics-driven approach?

A

Digital revenue increased by 50% in two years.

83
Q

What is the significance of asking the right business questions in data analytics?

A

It is necessary for achieving successful outcomes.

84
Q

Fill in the blank: The process of finding the best solution to a problem is known as _______.

A

[optimization]

85
Q

Fill in the blank: A metric that measures the percentage of people who click on a link or advertisement is called _______.

A

[click-through rate (CTR)]

86
Q

Fill in the blank: A statistical method for examining the relationship between a dependent variable and one or more independent variables is _______.

A

[regression analysis]

87
Q

What demographic is more likely to consume social media content?

A

Younger audiences

They tend to be more interested in soft content.

88
Q

What demographic is more likely to consume content on main websites?

A

Older audiences

They tend to be more interested in hard content.

89
Q

What is the significance of aligning content with audience preferences?

A

Increases engagement and advertising revenue.

90
Q

What is the first step in a data analytics project?

A

Identifying the project’s objectives.

91
Q

What must be identified after determining the project’s objectives?

A

Data requirements.

92
Q

What are key demographic variables influencing healthcare usage?

A

Age, gender, income, and education.

93
Q

What question might a healthcare provider ask regarding healthcare usage patterns?

A

What are the healthcare usage patterns for different age groups?

94
Q

What is a necessary aspect for a successful data analytics project?

A

Asking the right questions.

95
Q

What must be done to raw data before analysis?

A

Gathering, cleaning, and transforming it into a suitable format.

96
Q

What are some visualization techniques used in data analytics?

A
  • Bar charts
  • Line charts
  • Scatter plots
  • Heat maps
97
Q

What does the choice of visualization technique depend on?

A

The nature of the data and the insights communicated.

98
Q

What type of data is required for regression analysis?

A

Numerical data.

99
Q

What type of data is required for text analytics?

A

Unstructured text data.

100
Q

What is a primary benefit of data analytics techniques?

A

Ability to make more accurate and informed decisions.

101
Q

How can data analytics improve operational efficiency?

A

By identifying inefficiencies, redundancies, and areas for improvement.

102
Q

What advantage do data analytics techniques provide organizations?

A

Insights into customer preferences and behavior.

103
Q

What can organizations identify through data analytics?

A

Trends, patterns, and insights.

104
Q

What is the overall impact of data analytics techniques on organizations?

A

Improved decision-making, increased efficiency, and enhanced competitiveness.

105
Q

True or False: Organizations that invest in data analytics are better positioned to succeed.