Master Data Engineering using GCP Data Analytics

Partner: Udemy
Affiliate Name:
Area:
Description: Data Engineering is all about building Data Pipelines to get data from multiple sources into Data Lakes or Data Warehouses and then from Data Lakes or Data Warehouses to downstream systems. As part of this course, I will walk you through how to build Data Engineering Pipelines using GCP Data Analytics Stack. It includes services such as Google Cloud Storage, Google BigQuery, GCP Dataproc, Databricks on GCP, and many more.As part of this course, first you will go ahead and setup environment to learn using VS Code on Windows and Mac.Once the environment is ready, you need to sign up for Google Cloud Account. We will provide all the instructions to sign up for Google Cloud Account including reviewing billing as well as getting USD 300 Credit.We typically use Cloud Object Storage as Data Lake. As part of this course, you will learn how to use Google Cloud Storage as Data Lake along with how to manage the files in Google Cloud Storage both by using commands as well as Python. It also covers, integration of Pandas with files in Google Cloud Storage.GCP provides RDBMS as service via Cloud SQL. You will learn how to setup Postgresql Database Server using Cloud SQL. Once the Database Server is setup, you will also take care of setting up required application database and user. You will also understand how to develop Python based applications by integrating with GCP Secretmanager to retrieve the credentials.One of the key usage of Data is nothing but building reports and dashboards. Typically reports and dashboards are built using reporting tools pointing to Data Warehouse. As part of Google Data Analytics Services, BigQuery can be used as Data Warehouse. You will learn the features of BigQuery as a Data Warehouse along with key integrations using Python and Pandas.<
Category: Development > Data Science > Data Engineering
Partner ID:
Price: 199.99
Commission:
Source: Impact
Go to Course