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SnowFlake Course Overview
Snowflake is a Cloud Based data warehousing platform/solution that works as a SAAS provider. It is an analytics database built on Cloud and delivered as a Data Warehouse as a Service (DWAAS). Over 3000+ Organisations use this technology for their companies as it is one of the most cost-effective pricing solutions. Snowflake has made a revenue of 121.9 crores USD as of 2022. Learn Initial Configuration, Security and data management, Creating snowflake objects, stage the data files, Data Sharing and Validations in different formats. Snowflake leverages the functionality of an Innovative SQL Query engine with a flexible architecture natively established for the Cloud.
96%
of participants who met the conditions got placed
98%
Program Satisfaction
98%
Program Completion Raate
Advantages of this Course
- Snowflake's ability to evolve and innovate has given it an advantage in the cloud-computing market.
- We can share the data with external customers and vendors who do not have Snowflake accounts.
- Snowflake is a secure and provides easy access to all the data warehouse to business units. Geographies, Customers, Vendors, suppliers etc…
- It provides unlimited virtually performance and scale.
- It provides almost Zero maintenance services.
- It improve your security data encrypted from end to end with permission to revoke access at any time.
- Snowflake helps to reduce management effort by providing no indexing, Tuning performance, or optimization.
- You can store all your seme structured data like - Avro, XML, JSON, ORC etc…
Course Curriculum
- Snowflake Overview
- Architecture
- How to use the Snowflake UI & ecosystem
- What is Cloud
- Different Cloud Vendors
- Advantages of Cloud over On-Premise
- What is a Data Warehouse, and Why do we need a Data Warehouse?
- Database Vs Data Warehouse.
- Data Warehouse Architecture
- OLTP Vs OLAP
- What is ETL
- How different from traditional DB
- Quick start to the snowflake and accessing trial account
- Creating warehouse, DB, Schema, and tables
- Accessing different roles and using it
- Working with worksheets
- Understanding different type of accounts
- AWS and understanding S3 storage
- Snowflake architecture and caching
- AZURE and understanding blob storage
- GCP and understanding Bucket storage
- File formats
- Internal and external storage
- Internal and external stage
- Copy into usage
- Snowflake internal storage
- Accessing Cloud storage data into Snowflake (GCP, AZURE and AWS)
- Data unloading
- Accessing Snowpipe
- PUT and GET commands
- Bulk loading from cloud storage
- Continuous loading
- Snowflake Connector and use cases Python
- BI connectors use cases
- Other connectors hands-on
- Variant Data Type
- File format options
- Creating stages
- Loading JSON semi-structured data into SF tables
- Accessing JSON with select statement
- Creating Tasks
- Streams
- Accessing procedures with tasks
- Scheduling as per time with Different time zones
- Automate loading process Daily and Weekly
- Usage of sharing data
- Sharing data with different accounts
- Sharing data with non-SF accounts using reader accounts
- Importance of reader accounts
- Privileges in data sharing
- Challenges with cross-region sharing and understanding replication
- Connecting shared objects with BI tools
- Limitations with Data sharing
- Access Control Privileges for Cloned Objects.
- Cloning and Snowflake Objects
- Impact of DDL on Cloning
- Impact of DML and Data Retention on Cloning
- Access Control Privileges for Cloned Objects.
- Cloning and Snowflake Objects
- Impact of DDL on Cloning
- Impact of DML and Data Retention on Cloning
- Creating multi-users on large tables
- Performance techniques
- Result set cache
- Metadata cache
- Query data cache
- Best practices of using caching for performance and cost optimization
- Error Handling and Validations
- Snowflake Pricing model and selecting best Edition and Calculation of Credits usage
- Resource Monitoring
- Data Masking
- Partitioning and Clustering in snowflake
- Materialized View and Normal View
- Integration with Python
- Integration with AWS, Azure and Google Cloud
- Best Practices to follow