Dive into a course initially recorded live, making it engaging and interactive. You won’t just be passively learning; you’ll feel like you’re right there in the room with participants from the corporate world and learning solutions to REAL problems.
Here’s what you’ll learn in each unit:
Introduction to Business Intelligence
Overview of Business Intelligence
The journey from data to wisdom
Understanding the Business Intelligence process with Power BI
Understanding the Data Cycle
Exploring the limitations of traditional tools like Excel
Reviewing different licensing options in Power BI
Data Transformation Techniques in Power BI
Introduction to Power BI Query Editor
Common issues with data and how to identify them
Steps for effective data cleaning:
Removing columns and rows
Setting the first row as header
Changing data types, replacing values, and removing spaces
Handling errors, renaming and optimizing steps
Filling down missing values, splitting columns, and removing duplicates
Tips and tricks to automate data cleaning
Data Modeling and Enrichment
Basics of data modelling and building relationships
Understanding filter propagation and cardinality
Best practices in data model construction
Introduction to data enrichment: Creating calculated columns and measures
Basics of Data Visualization
Familiarization with native and custom visuals in Power BI
Hands-on creation of various charts (pie, line, bar), tables, and cards
Techniques for drilling down hierarchies and setting visual interactions
Formatting visuals and reports, including titles, legends, and axes
Utilizing slicers and different levels of filtering
Applying conditional formatting
Embedding images into reports
Publishing and Sharing Insights
Steps to publish reports and set default user experiences
Creating and managing workspaces for collaboration
Strategies for sharing reports effectively
Designing reports for mobile layouts
With over 15 years of exemplary experience in the field of data analytics and corporate training, Ali Noorani stands as a beacon of knowledge and inspiration. His journey, transitioning from a mechanical engineer to a Microsoft Certified Trainer, showcases his unparalleled adaptability and commitment to excellence. At the helm of AMZ Consulting, Ali has demonstrated extraordinary leadership and strategic foresight, propelling the company to the forefront of technology consulting. His profound expertise in Excel and Power BI, particularly in the complex arena of data modeling, sets him apart as a distinguished authority. Ali’s training methodology, marked by clarity and depth, has profoundly impacted the professional lives of over 2,000 participants from diverse industries, enabling them to unlock the potential of data in making informed business decisions.
Introduction
This fictitious dataset has been created to facilitate learning and practice in data analysis and visualization. It provides a rich collection of sales data, incorporating various dimensions such as time, geographical location, order methods, product types, and retailer information. This dataset is ideal for exploring sales trends and the overall performance of different products and retailers. This dataset will be used by the trainer in the accompanying videos, and it is predominantly used in the manual and exercise files unless explicitly mentioned otherwise in the manual.
Dataset Description
1. Sales Table:
Columns:
Trans Date: The date and time of the transaction.
RetCity: The city where the retailer is located.
Order method type: The method used to place the order (e.g., E-mail, Web, Sales visit).
Urgent?: Indicates whether the order was marked as urgent.
Retailer type: The type of retailer (e.g., Sports Store, Outdoors Shop).
Product Code: The code identifying the product sold.
Value: The monetary value of the sale.
Quantity Sold: The quantity of the product sold.
2. Country Table:
Columns:
Country: The name of the country.
City: The name of the city within the country.
3. Product Table:
Columns:
Product Code: The code identifying the product.
Product line: The product line to which the product belongs (e.g., Camping Equipment, Golf Equipment).
Product type/Product: The specific type or name of the product.
Product Cost: The cost of the product.
This comprehensive dataset enables detailed analysis of sales performance across various dimensions, making it an excellent resource for students, educators, and professionals looking to enhance their skills in data analytics and visualization.
This quiz serves as a qualifier to determine whether you have successfully comprehended the course material. It will aid in assessing your understanding of Power BI theory