Part 2: How the Snowflake Cloud Data Platform transforms organization?

By Mike Sargo

Chief Data and Analytics Officer and Co-Founder of Data Ideology  

The Snowflake Cloud Data Platform is one platform to build all your organization's data apps.

The advantages of leveraging Snowflake as your modern cloud data platform differs between the specific use cases of your organization. Here are some more of the critical capabilities that can help transform your organization:

Share Data Easily

Snowflake’s data sharing has transformed how organizations can distribute and consume shared data. The unique architecture of Snowflake’s data warehouse, which has been specifically built-for-the cloud, enables live data sharing without copying and moving data sets. Data providers allow secure and governed data shares to their data consumers. The data consumers can view and effortlessly combine it with their data sources. When a data provider inserts or updates data, the consumers always see the most up to date version in real-time. Data Providers can easily create one-to-one, one-to-many, and many to many data-sharing relationships. Data consumers (internal & external) can securely query read-only, centralized data with complete data integrity from a single, always accurate data source.

Time Travel

Snowflake time travel capability enables accessing historical data that was modified or deleted. You can view or seamlessly revert your database, tables, and schemas to any point within a defined period from the past for a user-determined retention period. Customers appreciate the ability to restore their data-related objects (tables, schemas, and databases) that may have been accidentally or intentionally deleted along with the unique capability to duplicate and back up data from critical points in the past.

Maximize AI, ML, and Data Science

Some of the traditional tools can limit how much data that data engineers can store and analyze. Snowflake’s cloud data platform can seamlessly integrate and support the applications that are relied upon by data scientists. Snowflake’s unlimited data storage and compute resources can rapidly scale to meet the demands of any user to support your advanced analytics use cases while integrations with Spark, Python, R, Java, and many of the leading data science tools such as DataRobot, Dataiku,, AWS Sagemaker, and Zepl.

Load Data Continuously with Snowpipe

Modern data-driven organizations deal with a broad range of continuously generated and streaming data sets. Snowpipe enables organizations to load data from files as quickly as they’re available in a stage. Snowpipe loads data from files in micro-batches, which make it available to users immediately, as opposed to manually executing COPY statements on a schedule to load larger batches of data. Snowpipe can load your data into Snowflake continuously as a serverless ingestion service.

Embedded Analytics

Our customers are developing and applying exceptional analytics experiences for their organizations. Traditional data warehouses and big data platforms struggle to seamlessly integrate data from multiple sources and deliver it to users in an easy to use manner. Complexity and inflexibility create challenges that add difficulty, cost, and delay to the efficient delivery of data-driven applications. Snowflake’s cloud data warehouse not only alleviates data warehouse management but also can effortlessly scale to support your organization as usage and concurrency expand. 

Snowflake’s cloud data platform can support all the data insights your organization needs.

Benefit from Snowflake's Ecosystem

Snowflake works with a wide range of industry-leading tools and technologies. These technologies can enable you to utilize Snowflake with an extensive network of connectors, drivers, programming languages, and utilities. Snowflake’s ecosystem provides native integrations with all major cloud vendors (Microsoft Azure, Amazone Web Services, and Google Cloud Platform), Data Integration Tools (Informatica, Matillion, FiveTran, SnapLogic, Talend, and more), Business Intelligence Tools (Microsoft Power BI, Tableau, and more), Advanced Analytics Tools (Spark, Databricks, R, and more), Security & Governance, SQL Development & Management, and Programmatic Interfaces (JDBC, ODBC, and more.)



Written by Mike Sargo
Mike Sargo is Chief Data and Analytics Officer and Co-Founder of Data Ideology with over 18 years of experience leading, architecting, implementing, and delivering enterprise analytics, business intelligence, and enterprise data management solutions.

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