The Complete Guide to Data Preparation for Analysis

Packt via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Paid Certificate Available
Duration & workload

8 hours
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you'll dive into essential frameworks and techniques for data preparation, exploring everything from data collection to cleaning. You’ll discover how to apply frameworks for mobile, web, and real-time data streaming, as well as cloud-based systems to collect and analyze data efficiently. The course offers in-depth exploration into survey design and data standardization, ensuring that you understand both the theory and practical applications of these concepts. The journey through this course begins with foundational knowledge, advancing through frameworks for collecting and standardizing data. You'll also work on hands-on projects that involve creating survey questions, administering surveys, and applying various cleaning techniques to real-world datasets. As you progress, the course builds on each module to ensure a smooth and comprehensive learning experience. This course is ideal for data professionals, analysts, or anyone involved in data analysis and preparation. A background in data science or information technology would be helpful but is not mandatory. The course is designed to be approachable while still providing deep, advanced insights into data preparation. By the end of the course, you will be able to effectively collect, standardize, clean, and prepare data for analysis using various frameworks and tools, ensuring the highest data quality and integrity.

Syllabus

Part 1 - Introduction - Data Collection Frameworks for Data Professionals

In this module, we will introduce you to the concept of data collection frameworks and their essential role in data preparation. We will explore where and why data collection is critical, with a focus on its application in decision-making processes.

Types and Frameworks of Data Collection

In this module, we will dive into the different types of data collection methods and frameworks. From mobile analytics to real-time streaming, you'll learn how each framework serves a specific purpose and enhances data-driven decision-making.

Business Context and Tools for Data Collection

In this module, we will explore the intersection of business growth and data collection needs. You’ll learn how to select the appropriate tools and frameworks based on business context and project objectives.

Part 2 - Introduction Survey Design Beginner to Pro - Framework and ChatGPT

In this module, we will introduce survey design, covering its fundamental principles and its diverse applications. We’ll also explore how ChatGPT can assist in creating and refining survey questions for better insights.

Introduction to the Survey Project

In this module, we will introduce you to the process of planning and executing a survey project. We’ll guide you through gathering background information and defining clear objectives for successful survey execution.

Creating Survey Questions

In this module, we will cover the art of creating effective survey questions. From brainstorming to crafting clear, relevant questions, we’ll teach you how to gather valuable insights through well-designed survey items.

Creating Questionnaire with ChatGPT

In this module, we will explore how to leverage ChatGPT for forming and refining survey questions. You will also learn how to design and implement the questionnaire using Google Forms for seamless data collection.

Survey Administration

In this module, we will cover the essential techniques for administering surveys. From logical branching to piloting and administrative methods, you’ll learn how to effectively manage and distribute surveys for optimal outcomes.

Part 3 - Introduction - Data Standardization Frameworks

In this module, we will introduce the concept of data standardization. You’ll learn how it ensures consistency and quality in your datasets, enabling more accurate analysis and insights.

Data Standardization Frameworks

In this module, we will dive into various data standardization frameworks. You'll explore data wrangling, blending, and transformation techniques, all aimed at preparing data for high-quality analysis.

Industry Standards and Its Frameworks

In this module, we will examine the industry standards for data preparation. You’ll gain insights into how data standardization works within general and complex frameworks to ensure consistent, high-quality data.

Part 4 - Introduction - Data Cleaning Frameworks and Techniques - Data Professionals

In this module, we will introduce the significance of data cleaning. You'll learn how data cleaning techniques ensure accuracy and reliability, preparing your data for in-depth analysis.

Key Aspects of Data Cleaning

In this module, we will explore the key aspects of data cleaning, including data profiling and error correction. You’ll gain the skills to identify and resolve issues, ensuring your data is accurate and ready for analysis.

Techniques of Data Cleaning

In this module, we will explore advanced data cleaning techniques, from handling missing data to data transformation. You will gain hands-on experience with tools that ensure your data is in top shape for analysis.