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Snowflake Data Engineer Training
Course Description This 3-day role-specific course covers the Snowflake key …
What you'll learn
Overview of Snowflake key features and architecture
Performance and cost optimization techniques using caching and high performing functions
Learn different UI and application methods of accessing Snowflake
Use the capabilities and best practices for working with semi-structured data in Snowflake Load, unload data sets and best practices
Tune queries and performance using advanced techniques such as data clustering and materialized views
Develop application for Snowflake including using comprehensive ANSI standard SQL support
Leveraging Snowflake SQL extensibility features such as time travel capabilities, user-defined functions and stored procedures
Snowflake Data Science Training
Course Description This 3-day class is ideal for Snowflake users …
What you'll learn
Collect and access data from Snowflake Data Marketplace and other sources
Manage and architect data lakes and real time streams
Employ Snowflake best practices for developing or querying semi-structured and other data types
Work with supervised and unsupervised machine learning models using some of the most relevant open source framework and libraries
Formulate data science and machine learning workflow and data pipelines
Manage and deploy machine learning models at scale with APIs
Visualize and collaborate on machine learning results
Snowflake Advanced Training
Course Description This 3-day course covers advanced Data Movement, Performance, …
What you'll learn
Evaluate Snowflakes advanced architectural concepts
Employ strategies and best practices for agile development
Discuss Snowflakes various ingestions methods for streaming data
Develop a methodology for performance tuning
Design a comprehensive program for ensuring user, network & data security
Share data in or outside of your organization securely
Snowflake Fundamentals 4-Day
Course Description This 4-day course covers the fundamental concepts, design …
What you'll learn
Illustrate the unique and differentiated architecture of the Snowflake Cloud Data Platform
Load and transform data
Evaluate Query Constructs and DDL & DML Operations
Review Snowflakes broad SQL support for data analysis
Describe how user and application access can be easily managed
Demonstrate best practices for working with semi-structured data
Discuss how Snowflake provides a unique approach to caching Examine the various ways to connect and interact with the Snowflake Platform
Employ Snowflake’s method for continuous data protection
Utilize Data Sharing to send your data in real-time to Customers and Partners
Scale your Virtual Warehouse for performance and concurrency
Explain the different ways you can manage and monitor your Snowflake account
Architecting on AWS – Accelerator
Course Description This course combines Architecting on AWS and Advanced …
What you'll learn
Make architectural decisions based on AWS architectural principles and best practices
Use AWS services to make your infrastructure scalable, reliable, and highly available
Use AWS Managed Services to enable greater flexibility and resiliency in an infrastructure
Make an AWS-based infrastructure more efficient to increase performance and reduce costs
Use the Well Architected Framework to improve architectures with AWS solutions
Architecting on AWS
Course Description In this authorized Amazon Web Services (AWS) course, …
What you'll learn
Making decisions based on the AWS-recommended architectural principles and best practices
Leveraging AWS services to make your infrastructure scalable, reliable, and highly available
Leveraging AWS managed services to enable greater flexibility and resiliency in an infrastructure
Making an AWS-based infrastructure more efficient in order to increase performance and reduce costs
Using the Well-Architected Framework to improve architectures with AWS solutions
To reinforce this material, you will also explore case studies with a variety of AWS infrastructure designs and strategies.
After the course, you will be fully equipped to build and scale a more efficient and reliable IT solution on the AWS cloud environment.
DevOps Engineering on AWS
Manage a variety of DevOps Philosophies with DevOps Engineering on …
What you'll learn
List the advantages of small DevOps teams
List the roles and responsibilities of the members of a typical small DevOps team
Leverage AWS Cloud9 to write, run and debug your code as well as share your cloud-based IDE with your dev team.
Build continuous integration/continuous delivery (CI/CD) pipelines including testing and security
Develop Git branching strategies and integrate with CI/CD pipeline for various environments
Use AWS CloudFormation to deploy development, test, and production environments for a software development project
Design and implement an infrastructure on AWS that supports DevOps development projects
Build a CI/CD pipeline for AWS CloudFormation templates
Establish collaboration by bringing together the workflows and responsibilities of development and operations
Host secure, highly scalable private Git repositories with AWS CodeCommit
Leverage Amazon Elastic Container Registry (Amazon ECR) to securely store Docker container images and integrate with AWS CodeBuild and Amazon Elastic Container Service (Amazon ECS).
Automate build, test, and packaging code with AWS CodeBuild
Integrate security in the CI/CD pipelines tools and services
Implement common deployment strategies such as “all at once,” “rolling,” and “blue/green”
Automate software deployments to Amazon Elastic Compute Cloud (Amazon EC2), on-premises computes, AWS ECS (Amazon EC2 /AWS Fargate), and AWS Lambda with AWS CodeDeploy
Automate your release pipelines (build, test, deploy) with AWS CodePipeline
Monitor an application and environment using AWS tools and technologies
DP-203T00-A: Data Engineering on Microsoft Azure
Course Description: In this course, the student will learn about …
What you'll learn
Explore compute and storage options for data engineering workloads in Azure
Design and Implement the serving layer
Understand data engineering considerations
Run interactive queries using serverless SQL pools
Explore, transform, and load data into the Data Warehouse using Apache Spark
Perform data Exploration and Transformation in Azure Databricks
Ingest and load Data into the Data Warehouse
Transform Data with Azure Data Factory or Azure Synapse Pipelines
Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
Optimize Query Performance with Dedicated SQL Pools in Azure Synapse
Analyze and Optimize Data Warehouse Storage
Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
Perform end-to-end security with Azure Synapse Analytics
Perform real-time Stream Processing with Stream Analytics
Create a Stream Processing Solution with Event Hubs and Azure Databricks
Build reports using Power BI integration with Azure Synpase Analytics
Perform Integrated Machine Learning Processes in Azure Synapse Analytics