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IT & SoftwareIT CertificationsSnowflake

Snowflake Masterclass[stored proc+demos+Best practices+Labs]

Master snowflake cloud data-warehouse with hands on exercises from real time expert.
Rating: 4.5 out of 54.5 (2,176 ratings)
12,444 students
Created by Pradeep H C
Last updated 1/2022
English
English [Auto]

What you'll learn

  • Snowflake architecture in detail.
  • How data processing happens in snowflake.
  • Secure data sharing in snowflake.
  • Understand different caching layers in snowflake.
  • Continues data load using snowpipe.
  • Clustering tables in snowflake and how it works under the hood.
  • Load data and unload data from AWS , GOOGLE and AZURE cloud
  • Loading unstructured data.
  • Snowflake internal stage and external stages.
  • Snowflake data sampling and its importance.
  • Detail overview about, snowflake clone , failsafe and data retention.
  • Unique features of Snowfalke ( time travel , undrop , table swap)
  • Scheduling using Tasks
  • Streams in snowflake
  • Materialized views
  • Best practices in snowflake
  • Snowpro certification compatible.
  • Snowflake stored procedures.
  • Data masking
  • Snowsight and warehosue utilization dashboard.
  • Snowflake access control.

Requirements

  • Familiarity with SQL language and basic knowledge on database.

Description


If you would like to understand how to build workflows using Airflow, Talend and Snowflake Please check out my new course,

Snowflake cloud database with ETL(Airflow+Python+Talend)


This course is the result of my over 4 years of experience working with Snowflake. Snowflake is a fantastic tool to handle huge volumes of data. You can load, query and export, and run transactional queries on TB's and PB's of data easily.

You don't have to worry about infrastructure setup, security, performance, tuning, Garbage collection, node failures etc etc...

if you have already worked with Spark with EMR or with Data bricks you will be amazed by snowflake performance and simplicity.

But there is a catch, if you are not fully aware of how things works in snowflake, you will easily loose control and end up writing costly queries and end up using many of snowflake features wrongly.

I mentioned costly queries because  snowflake is build for performance.

Costly queries and wrong design decisions in snowflake will sky rocket your snowflake bill. I have made lot of such mistakes and learned from those mistakes.

This course is an effort to walk you through such experiences so that you don't end up doing same mistakes which i did!!!

Few things can only be learned by experience you can't find them in documentations this course will expose such details to you.


Hope you join me in this journey...................


The course is broadly divided into 3 modules,

Module#1

    Lectures ------------>: 38

    Real time Demos----->: 11

    Assignments--------->: 10

    Quiz------------------>: 6


  •    This module will concretize snowflake fundamental concepts and architecture.

  •    By the end of this module you will be having very strong foundation about snowflake.

Module#2

    Lectures ------------>: 46

    Real time Demos----->: 31

    Assignments--------->: 14

    Quiz------------------>: 2


  •     In this module i will walk you through, different techniques and options to load and unload data

        in snowflake.

  •     By the end of this module, you will be having great confidence in using COPY command and

        different data processing objects in snowflake.

Module#3

    Lectures ------------>: 45

    Real time Demos----->: 35

    Quiz------------------>: 3


  •     In this module, we closely evaluate important features of snowflake.

  •     This module helps you to understand, how each feature works under the hood.

  •     Through this knowledge you will be in a better position to decide, when to use the feature and when not to use the snowflake features.


High level overview of all modules with sections details is given below,

In module#1,  

    > Snowflake environment setup.

    > Snowflake architecture.

    > Snowflake caching , micro-partitions, clusters.

    > Snowflake clustering deep dive.

    > Snowflake virtual warehouse layer.

    > Performance tuning and DB characteristics.

In module#2,

    > Loading data in snowflake.

    > Loading data using internal stage.

    > Load data from aws s3.

    > Load data from google gcs.

    > Load data from Azure.

    > Copy command options.

    > Working with copy command.

    > Assignments.

    > Loading unstructured data

In module#3,

   > Snowpipe in snowflake.

   > Data sharing in snowflake.

   > Time travel.

   > Fail safe.

   > Clone feature.

   > Data sampling.

   > Tasks in snowflake.

   > Streaming in snowflake.

   > Continuous data load.

   > Materialized views.

Who this course is for:

  • Developers planning to learn snowflake database.
  • Architects who want to understand best practices followed while using snowflake database.

Featured review

Daniel Upton
Daniel U.
20 courses
10 reviews
Rating: 4.5 out of 5a year ago
As I enter Section 3 of this course, I am already finding it to be excellent. So far, Pradeep has done a fine job of presenting both high-level architectural concepts with important details about the interface and query execution. As just one example, his code shows how to save cost when spinning up a compute cluster, using Auto Suspend, Auto Resume, and Suspend Time Out. If this course continues to be this good, I will surely raise it to 5 stars straight up!

Instructor

Pradeep H C
Data engineer
Pradeep H C
  • 4.5 Instructor Rating
  • 2,212 Reviews
  • 12,575 Students
  • 2 Courses

Pradeep has over 7 years of experience working in ETL and data warehousing.

He has great expertise on Snowflake enterprise database, Python, AWS cloud services(EC2,EMR,S3,LAMBDA,KINESIS) Hadoop, Talend and Informatica.

He has great experience in building data pipelines and building data products and services for customers by using advanced analytics.

He has good knowledge on data science and big data technologies. Currently he is working on building data pipelines using spark.

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