Data Analyst Fellowship

What will you learn

1. Microsoft Excel For Business Intelligence Analytics

Spreadsheet tools like Microsoft Excel are essential tools for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a working knowledge of Microsoft Excel and how to use it for analyzing data. Microsoft Excel is suitable for those who are interested in pursuing a career in Data Analysis or Data Science, as well as anyone looking to use Microsoft Excel for Data Analysis in their own domain. No prior experience with spreadsheets or coding is required.

2. Microsoft Power Business Intelligence (Power BI)

Microsoft Power BI is a tool that offers powerful business analytics, interactive visualizations, and business intelligence capabilities, wrapped in an interface simple enough for end-users to create their own reports and dashboards. Part of the Power Platform suite of Microsoft tools, Power BI enables you to pull together various data sources and use built-in AI features to create visually immersive, interactive dashboards and reports, with actionable insights, to help everyone make confident business decisions and drive your results. At the end of your training, you would have been empowered to discover insights hidden in your data.

3. Tableau

Become an expert at deriving valuable insights from large and varied data sets. You’ll learn to create impactful, interactive visualizations that communicate your findings in a meaningful way. As an Analyst, you are responsible for supporting your organization’s lines of business to deliver valuable insights from data. You are responsible for: Creating reports and dashboards for others in the organization to consume or iterate on, Performing ad-hoc exploration of data to highlight business opportunities, and Conducting meaningful data analysis to inform business decisions.

You will learn the skills you need to begin your Tableau Desktop journey. Learn core data literacy and Tableau concepts, and get guidance for creating your first Tableau workbook, empowering you to quickly get started with Tableau. You will learn how to connect to data sources, revise the properties of a data source, and save those customizations. Boost your skills for modifying data connections and working with multiple data sources. You'll also get the tools and knowledge to clean, shape, and combine data using Tableau Prep Builder. You will learn how to create views, dashboards, and stories using basic and advanced chart types. Structure your data by using groups, bins, and hierarchies, and apply sorting and filtering techniques to reveal additional insights. Round out your skills by designing dashboards that incorporate visual best practices. You will learn to use calculations, LOD expressions, and table calculations to create new views and insights. Create parameters and user controls, and show data trends and forecasts, as well as data distributions. You will understand Tableau roles and licenses, and the governance models and policies for publishing and managing content. Learn how to publish data and content on Tableau Server and Tableau Cloud, schedule extract refreshes, and manage published content.

4. MySQL for Data Analysis

You will learn how to use relational databases in Data and Business Analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for Data and Business Analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data yourself!

By the end of this course, you will have a clear understanding of how relational databases work and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world. MySQL is widely regarded as Data Analysts’ and Developers’ favorite database technology. It is the most used database technology in the world. Making you valuable to every organization.

5. Microsoft SQL SERVER

This training is designed for people who want to answer questions with data. For many, SQL is the "meat and potatoes" of data analysis—it's used for accessing, cleaning, and analyzing data that are stored in databases. It's very easy to learn, yet it's employed by the world's largest companies to solve incredibly challenging problems. This training is also meant for aspiring analysts who have no coding experience.

MS SQL Server is a crucial database solution that helps Data Analysts maintain the integrity of their data, more easily manage workloads of all sizes, and scale as needed. It is designed to be compatible with all major operating systems, and it supports text, images, sounds, and video, making it a very popular database for people and companies with diverse needs. At the end of your training, you will be well-equipped to interact with databases to carry out Data Analysis within this powerful software. Making you valuable to every organization.

6. Python for Data Analysis

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This training will take you from the basics of data analysis with Python to building and evaluating data models. You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will learn and practice using hands-on labs and projects. You will work with several open-source Python libraries, including Pandas and NumPy to load, manipulate, analyze, and visualize cool datasets. You will also work with SciPy and sci-kit-learn, to build machine-learning models and make predictions.

7. Problem-Solving Techniques for Root Cause Analysis & Business Optimization

The ability to identify the root cause of any problem cannot be undermined. This valuable skill is the distinction between successful problem-solving and symptom management. To obtain the right diagnosis of the root cause, you must take three key moves. This includes identifying the problem, the reasons for the problem, and the root cause itself. You can easily overcome almost every problem if you have the proper knowledge and skill to conduct a thorough analysis and implement the solution.

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