Snowflake is one of the most popular cloud data platforms. It allows data storage, data processing, and analytics at massive scale, with extremely less administrative effort, one of the key areas for any data platform is to build data pipelines. In this course, Moving Data with Snowflake, you’ll learn how to quickly & reliably, ingest the data into the tables of Snowflake database – by building Batch and Streaming pipelines in Snowflake. First, you’ll delve into each different data loading options in Snowflake. Then, you’ll see how the batch loading process works in Snowflake – how to connect to external data stores, like Azure Storage; and how to directly query the files in Snowflake. Next, you’ll explore how to work with structured, and semi-structured file formats, like CSV, JSON, and Parquet. finally, you’ll see how to process streaming data in Snowflake – how to continuously load the data using Snowpipe; and how to automate this loading process. By the end of this course, you’ll have the knowledge and skills, to Move Data with Snowflake, by building batch and streaming pipelines.
Author Name: Mohit Batra
Author Description:
Mohit is a Data Engineer, a Microsoft Certified Trainer (MCT) and a consultant. Mohit has 15+ years of extensive experience in architecting large scale Business Intelligence, Data Warehousing and Big Data solutions with companies like Microsoft and some leading investment banks. As an expert in his field, Mohit has often shared his knowledge in Azure, Spark, SQL Server and Power BI at various public forums and as a corporate trainer. Mohit truly loves to teach and enjoys producing high-quality,… more