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Getting Up To Speed
On Cloud Data Warehousing
Data warehousing: past to present
Understanding the benefits of a cloud data warehouse
Recognizing where cloud data warehousing fits in today’s
economy
Why The Modern Data
Warehouse Emerged
Adapting to increasing demands for data access and analytics
Adjusting to how data is created and used today
Tackling the challenges with new and improved technologies
The Criteria For
Selecting A Modern Data Warehouse
Choosing the right data warehouse solution
Getting a high performance-to-price ratio
Making data security and protection a priority
Comparing Cloud Data
Warehouse Solutions
Evaluating differences between cloud data warehouse options
Considering factors that affect performance
Choosing a solution that ensures data protection and
security
Gauging your savings in administrative costs
Six Steps To Getting
Started With Cloud Data Warehousing
Listing your data warehouse needs and success criteria
Considering all factors in the total cost of ownership
Taking your data warehouse for a test drive before you buy
Introduction To
Snowflake
Key Concepts & Architecture
Cloud Platforms
Snowflake Editions
Overview of Key Features
Overview of the Data Lifecycle
Continuous Data Protection
Connecting To
Snowflake
Overview of the Ecosystem
SnowSQL (CLI Client)
Installing SnowSQL
Configuring SnowSQL
Connecting Through SnowSQL
Using SnowSQL
JDBC Driver
Downloading / Integrating the JDBC Driver
Configuring and Using the JDBC Driver
JDBC Driver Diagnostic Service
ODBC Driver
Downloading the ODBC Driver
Installing and Configuring the ODBC Driver for Windows
ODBC Configuration and Connection Parameters
ODBC Driver API Support
ODBC Driver Diagnostic Service
Client Considerations
Diagnosing Common Connectivity Issues
Loading / Unloading
Data Into/From Snowflake
Overview of Data Loading/Unloading
Data Loading/Unloading Considerations
Preparing to Load/Unload Data
Bulk Loading/Unloading from a Local File System
Bulk Loading/Unloading from Amazon S3
Bulk Loading /Unloading from Microsoft Azure
Loading Continuously Using Snowpipe
Loading Using the Web Interface (Limited)
Querying Data in Staged Files
Querying Metadata for Staged Files
Transforming Data During a Load
Using Snowflake
Using the Web Interface
Virtual Warehouses
Databases, Tables & Views
Queries
Date & Time Data
Semi-structured Data
Binary Data
Snowflake Time Travel & Fail-safe
Sharing Data In
Snowflake
Introduction to Data Sharing
Data Providers
Getting Started with Data Sharing
Working with Shares
Using Secure Objects to Control Data Access
Managing Reader Accounts
Configuring a Reader Account
Data Consumers
Managing Your
Snowflake Account
System Usage & Billing
Understanding Snowflake Credit and Storage Usage
Understanding Snowflake Data Transfer Billing
Monitoring Account-level Credit and Storage Usage
Working with Resource Monitors
Parameter Management
User Management
Customer Specific
Topics
Informatica Cloud Services and Snowflake Integration
Introduction to Snowflake Connector
Snowflake Connector Task and Object Types
Informatica Cloud Hosted Agent
Snowflake Connections
Snowflake Connection Properties
Mappings and Mapping Configuration Tasks with Snowflake
Connector
Snowflake Objects in Mappings
Pushdown Optimization
Snowflake Sources in Mappings
Key Range Partitioning
Snowflake Targets in Mappings
Snowflake Lookups in Mappings
Rules and Guidelines for Snowflake objects
Snowflake is cloud based data warehouse and analytical tool.
With so many SAAS based Data warehouse applications available currently that
are competing against one another, Snowflake stands out among the crowd for it
uniqueness in design and approach. Snowflake works on an application that is
faster and easier to handle. Unlike other data warehouse systems Snowflake is
not built on Big data platforms rather it works on new SQL engine that is best
suited for cloud. Having one of the best ACID (atomicity, consistency,
isolation, and durability) complaint solutions. One of the USPs of Snowflake’s
unique capabilities is in its table structures wherein Micro–Partitions and
Data–Clustering are adopted Snowflake allows user to “time travel” i.e., track
data changes overtime and view changes made anytime in the past up to a 90–days
Some of the other features of Snowflake are
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