Podcast
Questions and Answers
Which of the following best describes the primary function of business analytics within an organization?
Which of the following best describes the primary function of business analytics within an organization?
- To automate the financial reporting process and reduce accounting errors.
- To improve marketing strategies through creative advertising campaigns.
- To support fact-based decision making using data and quantitative analysis. (correct)
- To manage employee relations and human resources using data-driven insights.
What is the role of data governance in the context of effective Business Intelligence (BI) and analytics?
What is the role of data governance in the context of effective Business Intelligence (BI) and analytics?
- To oversee the ethical considerations of employee surveillance and monitoring.
- To manage the physical security of data centers and IT infrastructure.
- To develop new algorithms for analyzing social media trends.
- To define roles, responsibilities, and processes to ensure data is trustworthy and reliable. (correct)
When is it MOST appropriate to use 'drill-down analysis'?
When is it MOST appropriate to use 'drill-down analysis'?
- When standardizing data entry processes across multiple departments.
- When needing to implement a new data security protocol for sensitive employee information.
- When needing to interactively examine data by exploring high-level summaries and increasing levels of detail. (correct)
- When needing to generate a quick summary report for upper management without detailed data.
Which activity is LEAST likely to be performed using spreadsheets within a business intelligence context?
Which activity is LEAST likely to be performed using spreadsheets within a business intelligence context?
In the context of data visualization, what does a 'conversation funnel' primarily represent?
In the context of data visualization, what does a 'conversation funnel' primarily represent?
What is the key benefit of Online Analytical Processing (OLAP)?
What is the key benefit of Online Analytical Processing (OLAP)?
What is the primary goal of data mining?
What is the primary goal of data mining?
If a dashboard shows a KPI that measures 'reduce the number of voluntary resignations', what essential components of a well-defined KPI are still needed?
If a dashboard shows a KPI that measures 'reduce the number of voluntary resignations', what essential components of a well-defined KPI are still needed?
Which of the following is the CORRECT sequence of phases in the Cross-Industry Standard Process for Data Mining (CRISP-DM)?
Which of the following is the CORRECT sequence of phases in the Cross-Industry Standard Process for Data Mining (CRISP-DM)?
Consider the statement: 'Improving customer satisfaction leads to increased brand loyalty.' What tool would you use to find the relationship between those two variables?
Consider the statement: 'Improving customer satisfaction leads to increased brand loyalty.' What tool would you use to find the relationship between those two variables?
What is the key advantage of self-service analytics?
What is the key advantage of self-service analytics?
Which of the following is MOST indicative of a 'data scientist'?
Which of the following is MOST indicative of a 'data scientist'?
Which of these data mining techniques involves identifying statistical rules to define relationships?
Which of these data mining techniques involves identifying statistical rules to define relationships?
What is the primary function of a dashboard in business analytics?
What is the primary function of a dashboard in business analytics?
Which of the following best describes the role of 'data visualization'?
Which of the following best describes the role of 'data visualization'?
In terms of linear regression, what key assumption needs to be true when working with a set of data?
In terms of linear regression, what key assumption needs to be true when working with a set of data?
Which of the following is NOT a tool listed to achieve benefits from BI and analytics?
Which of the following is NOT a tool listed to achieve benefits from BI and analytics?
What is a 'data cube', and how is it used in Online Analytical Processing (OLAP)?
What is a 'data cube', and how is it used in Online Analytical Processing (OLAP)?
Self-Service Analytics could result in proliferating 'data islands'. What are 'data islands'?
Self-Service Analytics could result in proliferating 'data islands'. What are 'data islands'?
A company wants to predict future sales based on historical data. Which data mining technique is MOST suitable for this task?
A company wants to predict future sales based on historical data. Which data mining technique is MOST suitable for this task?
Which of the following illustrates the use of data mining to improve customer retention?
Which of the following illustrates the use of data mining to improve customer retention?
What is the purpose of Business Intelligence?
What is the purpose of Business Intelligence?
Which of the following is LEAST associated with the role of a data scientist?
Which of the following is LEAST associated with the role of a data scientist?
Companies use linear regression for forecasting. What are the key assumptions that are used with linear regression? (Pick all that apply).
Companies use linear regression for forecasting. What are the key assumptions that are used with linear regression? (Pick all that apply).
Which of the following is a potential disadvantage of self-service analytics?
Which of the following is a potential disadvantage of self-service analytics?
What is the main goal of Business Intelligence?
What is the main goal of Business Intelligence?
Which of the following roles would need to master statistics, math, and computer programming?
Which of the following roles would need to master statistics, math, and computer programming?
Which feature is the MOST important to ensure the success of a self-service analytics tool?
Which feature is the MOST important to ensure the success of a self-service analytics tool?
A hotel wants to adjust room rates to maximize revenue. Which data mining technique could help them determine optimal pricing strategies?
A hotel wants to adjust room rates to maximize revenue. Which data mining technique could help them determine optimal pricing strategies?
Which technology best applies a 'what-if' analysis to evaluate various alternatives?
Which technology best applies a 'what-if' analysis to evaluate various alternatives?
In linear regression, what does finding the 'best-fitting straight line' through a set of observations accomplish?
In linear regression, what does finding the 'best-fitting straight line' through a set of observations accomplish?
What is a 'word cloud' in the context of data visualization, and how is it typically used?
What is a 'word cloud' in the context of data visualization, and how is it typically used?
Complete the following expression, which defines Key Performance Indicators (KPIs): direction + measure + ? + ?
Complete the following expression, which defines Key Performance Indicators (KPIs): direction + measure + ? + ?
How do Business Intelligence (BI) dashboards enhance organizational decision-making?
How do Business Intelligence (BI) dashboards enhance organizational decision-making?
What unique challenge does analyzing unstructured data present when using Business Intelligence (BI)?
What unique challenge does analyzing unstructured data present when using Business Intelligence (BI)?
How would a data scientist address the risk of 'proliferating data islands' within a self-service analytics environment?
How would a data scientist address the risk of 'proliferating data islands' within a self-service analytics environment?
A company notices a sudden, unexplained drop in sales. Which BI tool would be MOST effective for identifying the ROOT cause?
A company notices a sudden, unexplained drop in sales. Which BI tool would be MOST effective for identifying the ROOT cause?
Consider a scenario where a company is using data mining to identify seemingly unrelated products that are frequently purchased together. What is a POTENTIAL business VALUE of this analysis?
Consider a scenario where a company is using data mining to identify seemingly unrelated products that are frequently purchased together. What is a POTENTIAL business VALUE of this analysis?
Flashcards
Business analytics
Business analytics
Extensive use of data and quantitative analysis to support fact-based decision making.
Business intelligence (BI)
Business intelligence (BI)
Wide range of applications, practices, and technologies for data extraction, transformation, and presentation to support improved decision making.
Data scientists
Data scientists
Individuals who combine strong business acumen, analytical skills, and an understanding of data limitations to deliver real improvements.
Components for BI/Analytics
Components for BI/Analytics
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Spreadsheets
Spreadsheets
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Reporting/querying tools
Reporting/querying tools
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Data visualization
Data visualization
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Word cloud
Word cloud
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Conversion funnel
Conversion funnel
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Online analytical processing (OLAP)
Online analytical processing (OLAP)
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Data cubes
Data cubes
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Drill-down analysis
Drill-down analysis
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Linear regression
Linear regression
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Data mining
Data mining
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Association analysis
Association analysis
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CRISP-DM
CRISP-DM
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Measures / KPIs
Measures / KPIs
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Dashboard
Dashboard
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Self-service analytics
Self-service analytics
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Study Notes
Business Intelligence and Analytics
- Business analytics involves quantitative analysis and data to enable fact-based decision-making within organizations
- Business analytics is leveraged to:
- Improve understanding of current business performance
- Discover new business patterns
- Understand cause-and-effect of specific results
- Optimize current operations
- Predict future business results
- Business intelligence (BI) encompasses a diverse set of technologies and practices that extract, transform, integrate, visualize, analyze, interpret, and present data to facilitate improved decision making
- Data in BI is commonly compiled from both internal and external sources
- This data facilitates the creation of data collections like data warehouses, data marts, and data lakes
- BI and analytics help to:
- Detect fraud
- Improve forecasting
- Increase sales
- Optimize operations
- Reduce costs
Data Scientists
- Data scientists combine business acumen, analytical understanding, and knowledge of data, tools, and techniques to facilitate real improvements
- Data scientists:
- View situations from multiple angles
- Determine beneficial data and tools
- Often collaborate with business managers and specialists
- Are inquisitive
Educational Requirements for Data Scientists
- Rigorous educational requirements
- Mastery of statistics, math and computer programming
- May require an advanced degree
- Career-focused courses, degrees and certificates in analytical-related disciplines are offered such as database management, predictive analytics, BI, big data analysis and data mining
- Job prospects are very good for data scientists
Components for Effective BI and Analytics
- Data governance defines the roles, responsibilities and processes for ensuring data can be trusted and used
- Creative data scientists are a key component
- Effective Management teams must have strong commitments to data-driven decision making
Business Intelligence and Analytics Tools
- Spreadsheets
- Reporting and querying tools
- Data visualization tools
- Online analytical processing (OLAP)
- Drill-down analysis
- Linear regression
- Data mining
- Dashboards
Use of Spreadsheets
- Business managers import data into spreadsheet programs
- Spreadsheet programs perform operations using formulas
- Spreadsheets are commonly used to create reports and graphs
- Excel Scenario Manager performs "what-if" analysis
Reporting and Querying Tools
- Reporting and querying tools can present data that is easy to understand
- Presents data in formats like:
- Formatted data
- Graphs
- Charts
- These tools allow users to create their own data requests and format results without IT assistance
Data Visualization
- Data visualization uses pictorial or graphical formats of data to bring immediate impact to dull data
- Word clouds visually depict sets of words grouped by frequency of occurrence
- Conversation funnels graphically show the steps a customer takes when deciding to buy a product
Online Analytical Processing(OLAP)
- Online analytical processing is a way to analyze multidimensional data
- Gives many different perspectives
- OLAP helps identify issues and enables trend analysis
- Data cubes contain facts called measures, which are categorized by factors like time and location
- Using data cubes you can summarize unit sales of a specific item on a specific day
Drill-Down Analysis
- Drill-down analysis involves examining high-level data in increasing increments
- Example: A VP of Sales might drill down to view sales for each country; then, for each specific country for the last quarter; then see the sales for a specific country for a specific month of the quarter; finalising with a fourth level of analysis accomplished by drilling down to sales by product line for a particular country by month
Linear Regression
- A mathematical technique used to predict the value of a dependent variable
- Prediction is based on a single independent variable with linear relationship
- Consists of defining the best-fitting straight line through a set of observations of the dependent and independent variables
- Key assumptions
- Linear relationships between independent and dependent variables must exist
- Errors in the value of Y follow a normal distribution curve
- Errors in the value of Y are independent of one another
Data Mining
- BI tool utilized to explore data for hidden patterns
- Predicts future behaviors and trends for use in decision making
- Common data mining techniques are:
- Association analysis: a specialized set of algorithms sorts through data and forms statistical rules about relationships among the items
- Neural computing: historical data is examined for patterns that are then used to make predictions
- Case-based reasoning: historical if-then-else cases are used to recognize patterns
- Cross-Industry Process for Data Mining (CRISP-DM) involves a size-phase structured approach for planning data mining
Table 6.1 - Goals for each phase of CRISP-DM
- Business Understanding: Clarify the business goals, convert to predictive analysis and design project
- Data Understanding: Gather data, learn the data, identify any data quality problems
- Data Preparation: Select useable data, clean data and address quality issues
- Modeling: Applies selected modeling techniques
- Evaluation: Assess if the model achieves business goals
- Deployment: deploy the model into the decision-making process
Examples of Data Mining
- Use past responses to promotional mailings to identify consumers likely to take advantage of future mailings
- Examine retail sales data to identify seemingly unrelated products buyers often purchase together
- Monitor credit card transactions to identify likely fraudulent authorization requests
- Utilize hotel trends to adjust prices to maximize revenue
- Analyze behavior/ demographic data to identify potential customers to recruit
- Study demographic and characteristic data to focus future recruiting efforts
- How changes in DNA affect risk of developing diseases
Dashboards
-Track progress of strategies to attain organizational goals
- Measures also called key performance indicators (KPIs) with direction, measure, target and time frame
- Examples of well-defined KPIS:
- Increasing 5-year graduation rate for incoming freshers to 80% by 2022
- Answering customer service calls within 4 rings 90% of the time in the next 3 months
- HR to reduce voluntary resignations and terminations to 6% or less for the 2018 fiscal year onwards
Core Function of Dashboards
- Presents KPIs on the state of a process at a specific time
- Allows people to quickly and easily understand information
- Provides information to all levels of an organization to improve decisions
- Can be designed to draw real-time data
- Includes databases and spreadsheets
- Widely used BI includes Hewlett Packard, IBM, Information Builders, Microsoft, Oracle, and SAP.
Self-Service Analytics
- Gives users access to various data, training, techniques and processes from approved data sources
- Encourages nontechnical users to make decisions based on facts rather than intuition
- Ability to gather insights, analyse trends, uncover opportunities/ issues and quickly reports
- A well managed analytics program will allow Tech professionals to retain control over data while limiting staff
- Tools must be intuitive and easy to use
- End users easily access their own customized information and training
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