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Google Data Studio – Insights at a Glance with Google Data Studio
Google Data Studio – Insights at a Glance with Google …
What you'll learn
Week 1: Introduction to Google Data Studio and Data Visualization (4 Hours)
Session 1 (2 Hours): Fundamentals of Google Data Studio
Introduction to Business Intelligence and Data Visualization
Overview of Google Data Studio: Features and Capabilities
Setting Up and Navigating Google Data Studio
Session 2 (2 Hours): Connecting to Data Sources
Integrating Various Data Sources (Google Sheets, Analytics, SQL databases)
Understanding Data Source Fields and Data Types
Basic Data Transformations and Preparations
Week 2: Building Reports and Visualizations (6 Hours)
Session 3 (2 Hours): Creating Basic Reports and Charts
Designing Reports with Tables, Scorecards, and Basic Charts
Customizing Data Visualization Elements
Best Practices in Report Layout and Design
Session 4 (2 Hours): Advanced Visualization Techniques
Exploring Advanced Chart Types (e.g., Geo Maps, Scatter Charts)
Using Filters and Date Range Controls
Interactive Features in Reports (e.g., Drill Downs)
Session 5 (2 Hours): Enhancing Reports with Styling and Branding
Advanced Styling Options for Professional-Looking Reports
Adding Branding Elements and Custom Themes
Conditional Formatting for Enhanced Data Presentation
Week 3: Advanced Features and Business Applications (6 Hours)
Session 6 (2 Hours): Advanced Data Studio Features
Using Calculated Fields and Custom Formulas
Introduction to Blended Data and Data Joining
Implementing Row-Level Security and Access Controls
Session 7 (2 Hours): Data Exploration and Insights
Exploring Data with Explorer Mode
Using Data Studio for Business Analytics and Insights
Case Studies: Real-World Business Applications
Session 8 (2 Hours): Collaborating and Sharing in Data Studio
Collaborative Features in Google Data Studio
Sharing and Embedding Reports
Best Practices for Managing and Organizing Reports
Week 4: Practical Application and Capstone Project (4 Hours)
Session 9 (2 Hours): Integrating Google Data Studio in Business Strategy
Developing Data-Driven Business Strategies Using Reports
Discussing Ethical Considerations in Data Reporting
Strategies for Effective Data Storytelling in Business
Session 10 (2 Hours): Capstone Project and Course Wrap-Up
Developing a Comprehensive Business Intelligence Dashboard for a Real or Simulated Business Scenario
Presentation of Capstone Projects
Course Summary and Pathways for Further Learning
The course should include a mix of lectures, hands-on exercises, and case studies, with a strong emphasis on practical application using real-world business scenarios. The capstone project in the final week should involve creating a comprehensive business intelligence dashboard, allowing students to apply their learning in a realistic business context. This structure ensures MBA students not only acquire technical skills in Google Data Studio but also understand how to strategically apply these skills for business analysis and decision-making.
Free
Data Analytics and Statistical Analysis for MBA – From Data to Decisions: Advanced Statistical Techniques for MBAs
“Data Analytics and Statistical Analysis for MBA – From Data …
What you'll learn
Week 1: Introduction to Data Analytics and Basic Statistics (4 Hours)
Session 1 (2 Hours): Introduction to Data Analytics
Overview of Data Analytics in Business
Role of Data Analytics in Decision-Making
Introduction to Statistical Concepts
Session 2 (2 Hours): Basics of Descriptive Statistics
Measures of Central Tendency (Mean, Median, Mode)
Measures of Variability (Range, Variance, Standard Deviation)
Data Visualization Basics (Histograms, Box Plots)
Week 2: Exploratory Data Analysis and Inferential Statistics (6 Hours)
Session 3 (2 Hours): Exploratory Data Analysis (EDA)
EDA Techniques
Understanding Data Distributions
Introduction to Statistical Software (e.g., R, Python)
Session 4 (2 Hours): Probability and Probability Distributions
Basic Probability Concepts
Discrete and Continuous Distributions (e.g., Binomial, Normal)
Session 5 (2 Hours): Basics of Inferential Statistics
Sampling and Estimation
Hypothesis Testing Concepts
Introduction to Regression Analysis
Week 3: Advanced Statistical Techniques (6 Hours)
Session 6 (2 Hours): Linear Regression Analysis
Simple and Multiple Linear Regression
Interpreting Regression Output
Assumptions and Diagnostics in Regression
Session 7 (2 Hours): Time Series Analysis and Forecasting
Components of Time Series Data
Moving Averages, Smoothing Techniques
Introduction to ARIMA Models
Session 8 (2 Hours): Decision Trees and Clustering
Basics of Classification and Clustering
Introduction to Decision Trees
Basics of K-Means Clustering
Week 4: Application of Data Analytics in Business (4 Hours)
Session 9 (2 Hours): Data Analytics in Finance and Marketing
Case Studies in Financial Analytics
Market Analysis and Consumer Behavior Studies
Session 10 (2 Hours): Capstone Project and Course Wrap-up
Application of Learned Techniques to a Business Case
Group Project Presentation
Course Summary and Path Forward for Further Learning
Each session would ideally include a mix of lecture, discussion, and hands-on exercises using statistical software. The capstone project in the final session should be a comprehensive task that requires students to apply all the skills they've learned, ideally focusing on a real-world business scenario. This structure ensures that MBA students not only understand the theoretical underpinnings of statistical analysis but also how to apply these techniques in a business context.
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Promoting Ethical and Sustainable Business Practices in Research and Insight
This course is designed to provide participants with a comprehensive …
What you'll learn
Define ethical research practices and understand their significance in the business context.
Explore the principles of sustainable business and their role in responsible decision-making.
Learn how to conduct research with integrity, including data collection, analysis, and reporting.
Understand the ethical considerations related to participant consent, privacy, and confidentiality.
Gain insights into the social and environmental impact assessment in business research.
Analyze case studies of ethical and sustainable research practices in various industries.
Discuss the challenges and dilemmas faced by researchers in maintaining ethical standards.
Explore emerging trends and tools for ethical and sustainable research and insight.
Formulate strategies for integrating ethical and sustainable practices into business research.
Identify the potential benefits and long-term advantages of ethical and sustainable business practices.
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Maximizing Academic Publications in Research and Insight
This course is designed to help participants understand the significance …
What you'll learn
Recognize the importance of academic publications in research and insight.
Understand the types of academic publications, including journals, conferences, and books.
Learn the process of preparing and submitting research papers for publication.
Explore strategies for selecting suitable academic journals and conferences.
Gain insights into the peer-review process and addressing reviewers' feedback.
Analyze the ethical considerations and best practices in academic publishing.
Discuss the impact of academic publications on research dissemination and career advancement.
Explore tools and resources for tracking academic citations and impact.
Formulate strategies for maximizing the visibility and impact of academic research.
Develop skills for effective academic writing and communication.
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Mastering Data, Analytics, and Methodology in Research and Insight
This course is designed to equip participants with essential knowledge …
What you'll learn
Understand the role of data and analytics in research and insight.
Explore various data collection methods, including surveys, interviews, and experiments.
Learn data processing and cleaning techniques for research data.
Gain insights into data analysis tools and statistical methods.
Analyze the importance of selecting appropriate research methodologies.
Discuss the ethical considerations in data collection and analysis.
Explore the role of data visualization in communicating research findings.
Formulate strategies for hypothesis testing and drawing conclusions.
Develop skills for using statistical software for data analysis.
Apply the principles of effective data-driven decision-making in research and insight.
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Learning & Development in Entrepreneurship
This course is designed to provide participants with insights into …
What you'll learn
Understand the importance of learning and development in entrepreneurship.
Explore the key principles and concepts of entrepreneurial education.
Learn how to identify and nurture entrepreneurial skills and mindset.
Gain insights into the role of mentorship and guidance in entrepreneurial learning.
Analyze the challenges and opportunities in entrepreneurship education.
Discuss the ethical considerations in fostering entrepreneurship.
Explore the impact of experiential learning and real-world projects in entrepreneurship.
Formulate strategies for continuous learning and adaptation in the entrepreneurial journey.
Develop skills for effective communication and networking in entrepreneurship.
Apply the principles of lifelong learning and development in entrepreneurship.
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Introduction to Investment Banking
Investment banking is a financial sector that plays a crucial …
What you'll learn
Introduction to the Investment Banking Industry: Familiarize with the role, significance, and structure of investment banks.
Services Provided by Investment Banks: Understand the full spectrum of services, including mergers and acquisitions, underwriting, sales and trading, and asset management.
Regulatory Environment: Learn about the regulatory landscape and how it shapes the operations of investment banks.
Equity and Debt Financing: Gain insights into how companies raise capital through equity and debt, and the role of investment banks in this process.
Mergers and Acquisitions (M&A): Introduce the concepts of M&A and the steps involved in an M&A transaction from both the buy-side and sell-side perspectives.
IPO Process: Understand the stages of an Initial Public Offering, from pre-IPO preparation to post-IPO market performance.
Financial Modeling and Valuation: Get introduced to the basics of financial modeling and valuation techniques used in investment banking.
Risk Management: Learn about the risk factors in investment banking and the tools used to manage and mitigate these risks.
Investment Banking Strategy: Familiarize with the strategic considerations in investment banking, including deal origination and client relationship management.
Career Paths in Investment Banking: Explore the various roles within an investment bank and the career paths available.
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Introduction to Financial Planning and Analysis (FP&A)
Financial Planning and Analysis (FP&A) plays a pivotal role in …
What you'll learn
Understanding FP&A: Define FP&A within the context of corporate finance and explain its strategic importance to organizations.
Financial Statement Analysis: Learn to analyze and interpret financial statements for better planning and forecasting.
Budgeting Basics: Grasp the fundamentals of budgeting, including the creation and management of effective budget plans.
Forecasting Techniques: Understand various financial forecasting methods and their applications in FP&A.
Variance Analysis: Learn to perform variance analysis and its significance in the FP&A process.
Capital Budgeting and Investment Appraisal: Introduce concepts like Net Present Value (NPV) and Internal Rate of Return (IRR) for project evaluation.
Working Capital Management: Understand the management of working capital and its impact on a company’s liquidity and profitability.
Financial Modeling: Gain basic insights into creating financial models for scenario analysis and decision-making.
Key Performance Indicators (KPIs): Identify and evaluate KPIs relevant to FP&A activities.
Strategic Planning: Understand how FP&A contributes to long-term strategic planning within an organization.
