Data Wrangling for Business

Overview

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Welcome to Data Wrangling for Business. This course will cover data wrangling principles and techniques for business. Key topics include data extraction, profiling, cleansing, integration, transformation, and automating data processes for business purposes. In the course, you will apply principles and techniques using data transformation tools, programming languages, and data process automation tools. The course offers you an opportunity to learn how to embed appropriate communication mechanisms for collaboration to identify and resolve real-world data challenges revealed in datasets and business processes, creating business value in today’s disparate computing and dynamic business environment.

Syllabus

Course Welcome and Introduction to Data Wrangling and Relational Databases

In this module, you will learn about the structure of relational databases and how to use SQL queries for information retrieval, focusing on single-row and group functions. In the next module, you will build upon this foundation by exploring data manipulation and data joining techniques.

Managing and Retrieving Data with SQL

The module also highlights how effective data manipulation and joining contribute to the broader goals of data wrangling and preparation, ensuring that data is both well-organized and ready for analysis.

Data Profiling and Discovery

In this module, you will learn how to explore datasets using Python. You’ll practice techniques to inspect dataset structure (rows, columns, and data types), and detect missing, invalid, or inconsistent data. You will also learn how to generate descriptive statistics and distribution summaries, as well as interpret profiling results to guide data cleansing and improve overall data quality.

Data Cleansing

By the end of this module, you will be able to apply practical data cleansing techniques to improve data quality and make your analysis more accurate and trustworthy.

Data Transformation

In this module, you will learn how to transform raw data into clean, structured datasets that are ready to be linked with other relevant data for enrichment. To perform these tasks, you will continue your work with Python and explore later in upcoming modules, tools like Alteryx to enhance your data preparation and enrichment workflow.

Data Integration

This module emphasizes techniques for gathering, integrating, and transforming data from diverse sources. Hands-on exercises focus on automating data extraction from webpages and processing textual data, enabling the conversion of raw, unstructured information into structured, analyzable formats. By applying these methods, participants learn to create unified datasets that are ready for deeper analysis and the generation of meaningful insights.

Data Wrangling Automation

In this module, you will learn how to use the industry automation tool, Alteryx, to automate the processes of data transformation and data integration. This skill will help you in your professional career to ease and expedite data processing.