Combining and Shaping Data

سرفصل های دوره

This course covers both conceptual and practical aspects of pulling together from different data sources, with different schemas and orientations, into a cohesive whole using Excel, Python, and various tools available on the Azure cloud platform.

1. Course Overview

1. Course Overview

2. Exploring Techniques to Combine and Shape Data

1. Version Check

2. Module Overview

3. Prerequisites and Course Outline

4. Connecting the Dots- Combining and Shaping Data

5. Wide Form and Long Form Data

6. Joins

7. Aggregations

8. Summary

3. Combining and Shaping Data Using Spreadsheets

01. Module Overview

02. Load Data and Join Tables

03. Aggregation Operations

04. Join Tables Using Power Query

05. Convert CSV Data to Table Format

06. Convert Wide Form Data to Long Form

07. Pivot Tables for Summary Statistics

08. Unpivot Tables

09. Calculating Cumulative Sum and Ranks on Partitioned Data

10. Summary

4. Combining and Shaping Data Using SQL

1. Module Overview

2. Introducing the Azure SQL Database

3. Loading Data to Azure Blob Storage

4. Creating an Azure SQL Database and Tables

5. Loading Data Using Azure Data Factory Pipelines

6. Querying Data in SQL Using Aggregations

7. Performing Join Operations in SQL

8. Performing Pivot and Unpivot Operations in SQL

9. Summary

5. Combining and Shaping Data Using Python

01. Module Overview

02. Data Cleaning- Missing Data and Outliers

03. Getting Started with Azure Notebooks

04. Combining and Shaping Data Using Pandas

05. Identifying and Coping with Outliers

06. Detecting Outliers Using Z-scores

07. Handling Missing Values

08. Cleaning Data

09. Working with Imbalanced Data

10. Handling Imbalanced Data with Scikit Learn

11. Summary

6. Integrating Data from Disparate Sources into a Data Warehouse

01. Module Overview

02. Transactional and Analytical Processing on Azure

03. Creating an Azure SQL Data Warehouse and Uploading Files to Azure Blob Storage

04. Loading Data from Blob Store to the Data Warehouse

05. Loading Data from GCP Cloud Storage Buckets to the Azure SQL Data Warehouse

06. Enabling Resource Permissions to an Azure Active Directory App

07. Python Script to Transform Data Using Pyspark

08. Transform Data Using a Spark Activity

09. Copying Data from a Blob Storage Folder

10. Summary

7. Working with Streaming Data Using a Data Warehouse

1. Module Overview

2. Batch and Streaming Data

3. Types of Windows

4. Watermarks and the Notion of Time

5. Creating a Stream Analytics Job and a Power BI Pro Account

6. Configuring Input and Output for the Stream Analytics Job

7. Visualizing Streaming Data Using Power BI

8. Summary and Further Study

139,000 تومان

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تولید کننده: PluralSight