Microsoft via Coursera

Data Preparation and Management

Name: Data Preparation and Management
Rating: 5 (24 reviews)

5.024 ratings at Coursera

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Overview

Data Preparation and Management is designed to equip you with the essential skills needed to prepare and manage data effectively using Microsoft Power BI. Throughout this course, you'll learn how to connect, clean, and transform data from various sources to ensure its integrity and quality. You will explore the principles of Extract, Transform, Load (ETL) processes, data storage, and the importance of maintaining data accuracy. This course emphasizes practical applications, providing you with hands-on experience in managing real-world data scenarios. By the end of this course, you’ll be ready to confidently handle data preparation tasks and ensure that your data is ready for analysis and visualization.

This program is for anyone interested in data analytics and visualization; there are no prerequisites. To get the most out of the learning experience, it is recommended to follow the courses in sequence, as each one builds on the skills and knowledge gained in the previous ones. By the time you begin this course, you should have a strong understanding of different types of visualizations and their appropriate use, along with the ability to create cohesive and compelling reports in Power BI. You should also be capable of identifying and addressing common design problems in reports, producing audience-focused reports by understanding business needs.

Syllabus 4

Data sources 6 hours
In this module, you will learn how to set up data sources in Power BI. You’ll explore the different types of data sources available, from structured to unstructured data, and understand how to connect them to your Power BI environment. In this module you'll also cover the basics of connectors, trig…
Data transformation 5 hours
This module focuses on transforming raw data into a structured format suitable for analysis. You'll be introduced to Power Query, a tool within Power BI, and learn how to perform basic and advanced data transformations. You also cover essential techniques such as appending, merging, and cleaning da…
Data storage and processing 2.5 hours
In this module, you will explore the principles of data storage and processing within Power BI. You’ll learn how to configure data storage options, understand the implications of storage choices on performance, and ensure that your data is optimized for quick access and analysis. Additionally, as y…
Final project and assessment: Data Preparation and Management 3.5 hours
This module brings together all the concepts learned in the course through a hands-on project. You’ll be tasked with preparing and managing data for a simulated real-world scenario, applying your knowledge of data sources, transformation, and storage. In this capstone project you will test your abi…

Advantages and disadvantages

Advantages

Structured courses with graded quizzes, assignments and deadlines you can reset.
A shareable certificate from the university or company when you pay.
Financial aid is often approved for students in India (apply 15 days before you need it).
From Microsoft, a well-regarded name.
Self-paced: start any time.
A clear syllabus (4 parts) you can see before you start.
Hands-on: you build or practise, not just watch.

Disadvantages

Paid after a 7-day free trial (Coursera Plus or per course).
Some courses can be audited for free, but graded work and certificates need payment.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.