TalentLabs: Certified Associate in Business Analytics

UPDATE: I'm proud to announce that I've completed the Certified Associate in Business Analytics

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(Note: I have used mybinder together with nbgitpuller to share my Python coding interactively via this mybinder.org button: )

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A series of TalentLabs assignments submitted for my program: Certified Associate in Business Analytics.

The modules are as follows:

1. Career Workshop
2. Course Introduction and Data Collection
3. Preparing data for analysis
4. Data Analysis (Insight Generation)
5. Data Visualisation

My Learnings for each module:

1. Career Workshop

   • Acquire the skill of tailoring my resume to match each job application by incorporating all the key points I've found from the job description into it.
   • Learn how to write impactful job experience statements on my resume, by including “what”, “how” and “result” elements.

2. Data Collection

   • Understand how to define the problem effectively by asking questions with SMART framework. Asking good questions helps clarify the specific details or requirements of a data analysis project.
   • Learn about the importance of documentation for your data collected to build trust towards your stakeholders (e.g., management, customers).
   • Learn to prepare a data collection plan. A data collection plan is a document that explains what problem you're solving, what questions you need to answer, where you'll get the data, who'll collect it, how it'll be kept safe, and how any issues or limitations will be handled.
   • Understand how to read reports and collect data from Google Analytics 4.
   • Completed a Google Analytics 4 Case study which is to prepare a Data Analytics Plan for a Game Company

3. Data Wrangling

   • Wrangling and Cleaning data with Google Sheets
   • Clean Big Data with SQL in BigQuery
   • Become more familiar with pandas - a popular Python library
   • Wrangling with a messy shark attack dataset via Python. Key data cleaning tasks are covered such as identifying irrelevant columns, removing duplicates, imputing missing values, and fixing errors in data types, formats, and spelling. Learn more here or click this button for interactive Python notebook:

4. Data Analysis (Insight Generation)

   • Learn to use BigQuery SQL to aggregate and summarize data. Learn some SQL syntax like AVG, PERCENTILE_CONT, GROUP BY, HAVING and ORDER BY, etc.
   • Learn to use Python to do exploratory data analysis such as univariate, bivariate, and multivariate analysis
   • Use Python for A/B testing to find the most effective promotion strategies to maximize sales outcomes. For example, in this project, we use t-test to find Promotion 1 and Promotion 3 indeed outperform Promotion 2. Learn more here or click this button for interactive Python notebook:

5. Data Visualisation

   • Learn to visualize the business insights with visualization tools like Power BI and Tableau
   • Apply what I've learned in the previous modules such as data cleaning, explanatory data analysis, and data visualization skills to complete the final assignment.