Extract, Transform, and Load Data
5.0 /5- Offered byCoursera
Extract, Transform, and Load Data at Coursera Overview
Duration | 15 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Extract, Transform, and Load Data at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to the schedule
- Earn a certificate upon completion from Coursera
Extract, Transform, and Load Data at Coursera Course details
- This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL
- Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination. In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled
- The typical student in this course will have experience working with data and aptitude with computer programming
Extract, Transform, and Load Data at Coursera Curriculum
Extract Data
Course Intro: Extract, Transform, and Load Data
Structure of Data
Terms Describing Portions of Data
Big Data
Data Sources
Public APIs and Web Scraping
Data Read from Cloud Storage
Extract, Transform, and Load (ETL)
CSV Files
SQL Queries
NoSQL Queries
Data Consolidation and Joins
Overview
Open Datasets
Guidelines for Reading Data from CSV Files
Guidelines for Extracting Data with Database Queries
Inner Join Example
Guidelines for Consolidating Data from Multiple Sources
Extracting Data
Transform Data
Data Preparation and Cleaning
Types of Data and Data Operations
Continuous vs. Discrete Variables
Data Parsing
Data Irregularities
Correction of Data Formats and Date Conversion
Deduplication
Word Embedding
Image Data Representation
Overview
Guidelines for Parsing Data
Guidelines for Handling Irregular and Unusable Data
Guidelines for Correcting Data Formats
Guidelines for Deduplicating Data
Text Data Transformation Techniques
Guidelines for Transforming Data
Transforming Data
Load Data
Data Loading Considerations
Data Loading: Databases
Data Loading: DataFrames
Data Loading: Text Files
ETL Endpoints
Data Loading: Visualization Tools
Overview
Guidelines for Loading Data into Databases
Guidelines for Loading Data into DataFrames
Guidelines for Loading Data into Text Files
Guidelines for Configuring ETL Endpoints
Guidelines for Loading Data into Visualization Tools
Exploring Data Visualization Tools
Loading Data
Apply What You've Learned
Extract, Transform, and Load Data at Coursera Admission Process
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