Practical Analytics Chapter 1

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Questions and Answers

Which question can data analytics help answer?

How can I create a new business?

What has happened in the past? (correct)

What is the meaning of life?

What will definitely happen in the future?

Data analytics involves gathering data only in usable form.

False

What is one of the main processes involved in data analytics?

Cleaning up the data

Data analytics takes us from data to ________.

decision Signup and view all the answers

Which field does not contribute to data analytics?

Astrology Signup and view all the answers

Match the areas with their respective applications:

Medicine = Unique vocabulary and analytical applications Public services = Community analysis and planning Sports and Entertainment = Performance analysis Business = Market trends and analysis Signup and view all the answers

Data analytics can automate some actions resulting from data discoveries.

True Signup and view all the answers

What is the final goal of data analytics?

To support decision-making. Signup and view all the answers

What is a primary reason for the increased demand for employees with data analysis skills?

Growth in the amount of data available Signup and view all the answers

Analytics is only performed by employees with formal training in data analysis.

False Signup and view all the answers

Name an area where analytics is used in retail.

Pricing strategies Signup and view all the answers

In marketing, analytics is used primarily for ______.

targeted marketing Signup and view all the answers

Match the following applications of data analytics with their corresponding fields:

Medicine = Risk factor identification Sports = Player performance analysis Law Enforcement = Criminal activity patterns Fraud Prevention = Credit card fraud detection Signup and view all the answers

Which of the following is NOT a use of business analytics?

Random employee assignments Signup and view all the answers

Analytics is irrelevant in government resource allocations.

False Signup and view all the answers

How is data analytics used in sports?

For player acquisitions and analysis of player performance. Signup and view all the answers

Who are the co-CEOs of Global Bike Company?

John Davis and Peter Weiss Signup and view all the answers

Global Bike Company sells directly to consumers.

False Signup and view all the answers

What type of data does Global Bike Company use an integrated system to manage operations?

Master data and transactional data Signup and view all the answers

Global Bike Company primarily targets the _______ and prosumer cyclist market.

professional Signup and view all the answers

Match the employees with their business questions:

Nina Kane = What data do I need to evaluate sales, discover trends, and identify opportunities? Donna Vasant = Is an electric bike a viable and profitable new product? Jessi Mard = Are profit margins in line with expectations? Signup and view all the answers

What type of products does Global Bike Company sell?

High-quality bicycles and cycling accessories Signup and view all the answers

Nina Kane is responsible for international sales at Global Bike Company.

False Signup and view all the answers

What is one potential new product idea mentioned for Global Bike Company?

Bike-integrated video cameras Signup and view all the answers

What is data analytics?

Data analytics is a process that involves identifying the problem, gathering relevant data, cleaning the data, loading it into data storage models, manipulating it to discover trends, and making decisions based on those insights. Signup and view all the answers

Which of the following is NOT a step in the data analytics process?

Hiding the results Signup and view all the answers

Data and information can be used interchangeably.

False Signup and view all the answers

What leads to the creation of knowledge in data analytics?

Knowledge is created when information is learned from data. Signup and view all the answers

Who is a practitioner of data science called?

Data scientist Signup and view all the answers

Which area does data analytics NOT support?

Cooking Signup and view all the answers

Data analytics is a subset of ___ science.

data Signup and view all the answers

What is the relationship between analytics, statistics, and domain knowledge?

Analytics is focused on applying models from statistics and domain knowledge to analyze data. Signup and view all the answers

What is a main benefit of digital transformation in businesses?

It enhances business processes using data analytics. Signup and view all the answers

Match the following applications of analytics with their corresponding fields:

Retail = Pricing strategies and product placement Manufacturing = Demand forecasting Marketing = Targeted marketing campaigns Government = Census data collection Signup and view all the answers

What are the three levels of responsibility in data analytics skills?

<ol> <li>Data Scientist, 2. Data Analyst, 3. Business Users/Managers</li> </ol> Signup and view all the answers

How can we become more efficient in the manufacturing processes?

By analyzing current methods and implementing improvements. Signup and view all the answers

Is the quality of raw materials affecting production?

True Signup and view all the answers

What process is covered in detail in Chapter 5?

Slicing and Dicing Signup and view all the answers

Can the manufacturing plant meet sales demand?

Answer varies depending on current production capabilities and sales forecasts. Signup and view all the answers

Data scientists usually create new models for all analysis goals.

False Signup and view all the answers

What is the primary purpose of applying a model to a dataset?

To analyze the dataset and present results often in visual form. Signup and view all the answers

Is the manufacturing facility set up to reduce unnecessary material movements?

True Signup and view all the answers

What form do results typically take after a model is applied?

Visualizations such as charts Signup and view all the answers

How does the production of IoT bicycles affect capabilities elsewhere in the facility?

Production can strain resources or improve efficiencies in other areas depending on demand and resource allocation. Signup and view all the answers

What must be checked against test data when reviewing results from predictive data models?

Deviations from acceptable model parameters. Signup and view all the answers

What percentage of orders is shipping within 24 hours of order receipt?

Percentage varies; requires current shipping data. Signup and view all the answers

GB solely focuses on manufacturing and selling bicycles.

False Signup and view all the answers

How many orders have not shipped within 24 hours of receipt and why?

Number varies; requires shipping logs. Signup and view all the answers

How many products were damaged during the packing and shipping process?

Number varies; requires damage reports. Signup and view all the answers

Did any orders ship to the incorrect customer or address?

True Signup and view all the answers

GB specializes in selling high-end bicycles and biking ______.

accessories Signup and view all the answers

Which component is essential for generating insights in analytics?

Domain Knowledge Signup and view all the answers

How can shipping problems be avoided in the future?

By improving shipping processes and communication with carriers. Signup and view all the answers

What does GB's analytics strategy rely on?

Data-driven decision-making. Signup and view all the answers

What is data analytics?

A process of gathering data, cleaning it, and making it usable for analysis. Signup and view all the answers

The demand for individuals with data analysis skills is decreasing.

False Signup and view all the answers

What does the analytics process involve?

A 10-step cycle beginning with goal setting and ongoing improvements. Signup and view all the answers

What is data analytics?

Data analytics is a process that involves identifying problems, gathering relevant data, cleaning the data, loading it into data storage models, manipulating it to discover trends and patterns, and making decisions based on those insights. Signup and view all the answers

Data becomes ______ when it reveals the causes or results of an event.

information Signup and view all the answers

What role does wisdom play in the analytics process?

Wisdom is the deep understanding of underlying principles and behaviors acquired over time, which helps in making informed decisions. Signup and view all the answers

Data analytics is primarily concerned with creating algorithms and models.

False Signup and view all the answers

Why is studying data analytics important?

Studying data analytics is important because it addresses the growing demand for skilled analysts who can interpret data to drive digital transformation in businesses. Signup and view all the answers

What are the three areas of responsibility in data analytics skills?

All of the above Signup and view all the answers

What are some applications of analytics in retail?

Analytics in retail is used for pricing, timing of pricing strategies, amount of discounts, product placement, and upselling and cross-selling. Signup and view all the answers

What kind of data analysis assists in manufacturing planning?

Demand forecasting Signup and view all the answers

What is a significant benefit of analytics in financial investing?

Determining acceptable investment risks Signup and view all the answers

How does data analytics play a role in fraud prevention?

Data analytics enables investigators to flag unusual activities for further investigation in fraud cases. Signup and view all the answers

What step in the analytics methodology involves defining goals and outcomes?

Identify goals Signup and view all the answers

What is the process of analyzing data called?

Slicing and dicing. Signup and view all the answers

What skills are needed to design a new data model?

Strong mathematical and analytical skills. Signup and view all the answers

Predictive models do not require validation against test data.

False Signup and view all the answers

What visualization techniques are mentioned for presenting findings?

All of the above Signup and view all the answers

How can we become more efficient in the manufacturing processes?

By optimizing workflows, improving resource allocation, and utilizing better technology. Signup and view all the answers

Is the quality of raw materials affecting production?

Yes, poor quality raw materials can lead to defects and increased waste in the production process. Signup and view all the answers

Is the manufacturing facility set up to reduce unnecessary material movements and encourage efficiency in the production process?

Yes, an efficient layout minimizes material handling and optimizes workflow. Signup and view all the answers

What percentage of orders is shipping within 24 hours of order receipt?

This percentage varies based on operational efficiency. Signup and view all the answers

How many products were damaged during the packing and shipping process?

The number should be tracked to identify areas for improvement. Signup and view all the answers

How many orders were damaged by the shipping company?

This should be tracked to hold the shipping company accountable. Signup and view all the answers

What is the analytics process?

A 10-step cycle beginning with goal setting and continuing with iterative improvements. Signup and view all the answers

What does data analytics entail?

Gathering data from various sources and making it usable for analysis. Signup and view all the answers

What skills are in high demand for data analysis?

Skills that facilitate effective data collection, analysis, and interpretation. Signup and view all the answers

Data analytics is used exclusively in business applications.

False Signup and view all the answers

Study Notes

Data Analytics Overview

Data Analytics answers critical questions regarding past events, future predictions, and actionable insights.
The process includes gathering, cleaning, storing, and manipulating data to derive information.
Involves collaboration of statistics, computer science, and domain-specific knowledge.

Importance of Studying Analytics

Increasing demand for employees skilled in data analysis due to growth in data availability.
Provides strategic advantages to organizations.

Users of Analytics

Analytics is utilized at various organizational levels, often by individuals without formal training.

Business Applications of Analytics

Retail: Pricing strategies, product placements, and discount plans.
Manufacturing: Demand forecasting and production planning.
Marketing: Targeted campaigns based on data insights.
Supply Chain: Vendor selection and distribution cost optimization.
Customer Service: Tailored service offerings and support.
Government: Resource allocation and compliance analysis.

Other Fields Using Analytics

Science: Key for data interpretation across scientific disciplines.
Medicine: Identifying risk factors and creating treatment plans.
Sports: Evaluating player performance and acquisition strategies.
Fraud Detection: Monitoring for credit card fraud.
Law Enforcement: Analyzing crime patterns for resource management.
Social Media: Detecting misinformation and false narratives.

Global Bike Company (GB)

Co-CEOs: John Davis and Peter Weiss.
Specializes in high-quality bicycles and accessories, targeting professional and prosumer markets.
Sales operations focused on partnerships with retailers rather than direct consumer sales.

Data Types at GB

Master Data: Entities like customers, vendors, products, and employees.
Transactional Data: Events such as sales, purchases, and payments.
Utilizes an integrated ERP system to manage operations efficiently.

Business Questions from GB Employees

U.S. Sales Manager: Focused on market share competition, sales trends, motivational strategies, and supply chain delays.
Business Analyst: Exploring new market opportunities, potential products, and implications of internet sales.
Controller: Assessing profit margins, operational efficiencies, and payment speed from customers.

Data Analytics Overview

Data analytics is a structured process that transitions from data collection to decision making, involving problem identification, data gathering, cleaning, storage, manipulation, and insight derivation.
It addresses critical questions related to past events, reasons behind them, future predictions, and actionable responses.
Distinction between data and information is essential: data are raw facts, while information results from data analysis revealing patterns and insights.

Knowledge and Wisdom

Knowledge emerges from understanding information, facilitating the identification of underlying factors affecting outcomes, leading to better decision-making.
Wisdom is developed over time through cumulative knowledge, aiding in forming strategic decisions aligned with organizational goals.

Evolution of Data Analytics

The field has evolved from strict statistical calculations to a multidisciplinary domain incorporating statistics, computer science, and specific industry expertise.
Data science, encompassing data analytics, utilizes computational techniques to extract valuable knowledge from large datasets.

Importance of Data Analytics

The significance of data analytics spans various fields, impacting decision-making across industries, and driving digital transformation.
Companies investing in data analytics aim to maintain competitive advantage, with 89% acknowledging risks for those lacking strong analytics strategies.
Continuous demand for skilled data analysts and scientists persists, with many companies reporting shortages in expertise.

Analytical Skill Levels

Three primary categories of analytical roles exist:
- Data Scientists: Highly specialized, skilled in advanced mathematics and programming.
- Data Analysts: Skilled in data analysis, typically possessing advanced degrees in business with quantitative focuses.
- Business Users: Most data analysis is conducted by managers without formal training in analytics.

Applications of Analytics

Retail: Used for pricing strategies, product placement, and customer behavior analysis.
Manufacturing: Demand forecasting aids in production planning.
Marketing: Predictive analytics enables targeted campaigns based on customer behavior insights.
Supply Chain: Optimizes supplier selection and distribution costs.
Customer Service: Enhances customization of support based on historical data.
Government: Facilitates demographic data collection for better resource allocation.
Utilities: Predicts energy demand and manages diverse power sources.
Medicine: Identifies risk factors and patterns for chronic diseases; aids in disease prevention efforts.
Sports: Coaches utilize analytics for performance improvement and strategy development.
Fraud Prevention: Enables detection and prevention of fraudulent activities like credit card fraud.

Analytics Methodology

The analytics process involves several key steps:
- Identify goals: Define clear objectives for data analysis.
- Gather data: Collect data from various sources such as information systems, experiments, or surveys.
- Design model: Choose an analytical approach, often requiring user-defined models for unique data sets.
- Apply model: Use tools to implement chosen models and generate results.
- Review results: Validate findings against expected outcomes, refining models as necessary.
- Present findings: Share results using various visual formats, aiding in comprehension and decision-making.

Benefits and Challenges

The framework of analytics encompasses enablers (technology, tools), benefits (improved performance, decision-making), and skilled personnel.
Use of analytics not only supports business operations but also fosters innovations and advancements across various domains.

Overall, the pervasive role of data analytics in contemporary society highlights its critical importance in making informed decisions and driving business success.### Data Analytics Overview

Analytics integrates computer technology, domain expertise, and statistics to generate insights.
Domain knowledge is essential for interpreting analyses, leading to informed decision-making.
Insights from data analysis help in crafting effective strategies, which are then implemented as actions.
Success of these actions is periodically measured to enhance future processes, initiating a continuous improvement cycle.

Global Bike Company (GB) Introduction

Founded through a merger in 2000 between John Davis and Peter Weiss, catering to professional and "prosumer" cyclists.
Renowned for carbon composite frames, offering high-end mountain and touring bikes.
Additional products include biking accessories: helmets, first aid kits, shirts, and water bottles.

Business Transformation

Experienced a digital transformation starting in 2015, initially focusing on IoT-enabled bicycles.
Shifted towards a profitable IoT bike-sharing model launched in July 2018, moving away from direct bicycle sales to rental services.
This strategic pivot helped GB capitalize on urban mobility trends, creating a new revenue stream.

Organizational Structure

Co-CEOs John Davis and Peter Weiss oversee approximately 100 employees, primarily in the U.S. and Germany.
Headquarters in Dallas, supporting product manufacturing and distribution; subsidiaries include GB Europe and Global Bike Sharing.
GB Europe, based in Heidelberg, handles R&D and manufacturing for the European market.

Data Management

Transactional data includes details such as order time, salesperson, product types, and payment terms.
Master data represent stable business entities like customers and products, facilitating consistent analytics.
Historical sales data spans 2007-2018, capturing trends through significant economic events.

Employee Overview

Employees leverage analytics to drive business strategies and operations, each facing unique challenges:
- Nina Kane (U.S. Sales Manager): Focuses on market competition, sales strategy, and team motivation.
- Donna Vasant (Business Analyst): Explores new markets and product lines.
- Alistair Lee (VP of Bike Sharing): Assesses bike-sharing program growth and customer experiences.
- Jessi Mard (Corporate Controller): Monitors profit margins and accounting efficiencies.
- Peter Pollard (Production Manager): Evaluates manufacturing efficiency and quality issues.
- Tony Liu (Shipping Coordinator): Ensures rapid shipping of orders.
- Bruce Hewlett (Shipping Manager): Analyzes shipping delays and product damages.

Challenges and Questions

Each employee utilizes analytics to answer pressing business questions and strategize improvements.
Identified challenges include market trends, product innovations, and operational efficiencies across various departments.

Summary of Data Analytics Importance

The increasing volume of data necessitates skilled data analysts in diverse fields.
A ten-step analytics process cycle highlights the ongoing nature of setting and refining business goals.

Data Analytics Overview

Data analytics is a structured process that transitions from data collection to decision making, involving problem identification, data gathering, cleaning, storage, manipulation, and insight derivation.
It addresses critical questions related to past events, reasons behind them, future predictions, and actionable responses.
Distinction between data and information is essential: data are raw facts, while information results from data analysis revealing patterns and insights.

Knowledge and Wisdom

Knowledge emerges from understanding information, facilitating the identification of underlying factors affecting outcomes, leading to better decision-making.
Wisdom is developed over time through cumulative knowledge, aiding in forming strategic decisions aligned with organizational goals.

Evolution of Data Analytics

The field has evolved from strict statistical calculations to a multidisciplinary domain incorporating statistics, computer science, and specific industry expertise.
Data science, encompassing data analytics, utilizes computational techniques to extract valuable knowledge from large datasets.

Importance of Data Analytics

The significance of data analytics spans various fields, impacting decision-making across industries, and driving digital transformation.
Companies investing in data analytics aim to maintain competitive advantage, with 89% acknowledging risks for those lacking strong analytics strategies.
Continuous demand for skilled data analysts and scientists persists, with many companies reporting shortages in expertise.

Analytical Skill Levels

Three primary categories of analytical roles exist:
- Data Scientists: Highly specialized, skilled in advanced mathematics and programming.
- Data Analysts: Skilled in data analysis, typically possessing advanced degrees in business with quantitative focuses.
- Business Users: Most data analysis is conducted by managers without formal training in analytics.

Applications of Analytics

Retail: Used for pricing strategies, product placement, and customer behavior analysis.
Manufacturing: Demand forecasting aids in production planning.
Marketing: Predictive analytics enables targeted campaigns based on customer behavior insights.
Supply Chain: Optimizes supplier selection and distribution costs.
Customer Service: Enhances customization of support based on historical data.
Government: Facilitates demographic data collection for better resource allocation.
Utilities: Predicts energy demand and manages diverse power sources.
Medicine: Identifies risk factors and patterns for chronic diseases; aids in disease prevention efforts.
Sports: Coaches utilize analytics for performance improvement and strategy development.
Fraud Prevention: Enables detection and prevention of fraudulent activities like credit card fraud.

Analytics Methodology

The analytics process involves several key steps:
- Identify goals: Define clear objectives for data analysis.
- Gather data: Collect data from various sources such as information systems, experiments, or surveys.
- Design model: Choose an analytical approach, often requiring user-defined models for unique data sets.
- Apply model: Use tools to implement chosen models and generate results.
- Review results: Validate findings against expected outcomes, refining models as necessary.
- Present findings: Share results using various visual formats, aiding in comprehension and decision-making.

Benefits and Challenges

The framework of analytics encompasses enablers (technology, tools), benefits (improved performance, decision-making), and skilled personnel.
Use of analytics not only supports business operations but also fosters innovations and advancements across various domains.

Overall, the pervasive role of data analytics in contemporary society highlights its critical importance in making informed decisions and driving business success.### Data Analytics Overview

Analytics integrates computer technology, domain expertise, and statistics to generate insights.
Domain knowledge is essential for interpreting analyses, leading to informed decision-making.
Insights from data analysis help in crafting effective strategies, which are then implemented as actions.
Success of these actions is periodically measured to enhance future processes, initiating a continuous improvement cycle.

Global Bike Company (GB) Introduction

Founded through a merger in 2000 between John Davis and Peter Weiss, catering to professional and "prosumer" cyclists.
Renowned for carbon composite frames, offering high-end mountain and touring bikes.
Additional products include biking accessories: helmets, first aid kits, shirts, and water bottles.

Business Transformation

Experienced a digital transformation starting in 2015, initially focusing on IoT-enabled bicycles.
Shifted towards a profitable IoT bike-sharing model launched in July 2018, moving away from direct bicycle sales to rental services.
This strategic pivot helped GB capitalize on urban mobility trends, creating a new revenue stream.

Organizational Structure

Co-CEOs John Davis and Peter Weiss oversee approximately 100 employees, primarily in the U.S. and Germany.
Headquarters in Dallas, supporting product manufacturing and distribution; subsidiaries include GB Europe and Global Bike Sharing.
GB Europe, based in Heidelberg, handles R&D and manufacturing for the European market.

Data Management

Transactional data includes details such as order time, salesperson, product types, and payment terms.
Master data represent stable business entities like customers and products, facilitating consistent analytics.
Historical sales data spans 2007-2018, capturing trends through significant economic events.

Employee Overview

Employees leverage analytics to drive business strategies and operations, each facing unique challenges:
- Nina Kane (U.S. Sales Manager): Focuses on market competition, sales strategy, and team motivation.
- Donna Vasant (Business Analyst): Explores new markets and product lines.
- Alistair Lee (VP of Bike Sharing): Assesses bike-sharing program growth and customer experiences.
- Jessi Mard (Corporate Controller): Monitors profit margins and accounting efficiencies.
- Peter Pollard (Production Manager): Evaluates manufacturing efficiency and quality issues.
- Tony Liu (Shipping Coordinator): Ensures rapid shipping of orders.
- Bruce Hewlett (Shipping Manager): Analyzes shipping delays and product damages.

Challenges and Questions

Each employee utilizes analytics to answer pressing business questions and strategize improvements.
Identified challenges include market trends, product innovations, and operational efficiencies across various departments.

Summary of Data Analytics Importance

The increasing volume of data necessitates skilled data analysts in diverse fields.
A ten-step analytics process cycle highlights the ongoing nature of setting and refining business goals.

Studying That Suits You

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Description

Explore the fundamentals of Data Analytics in this quiz based on Chapter 1. Understand how data analytics helps us answer critical questions about past, present, and future events. Delve into the potential of automation in the analytics process.