Snowflake Horizon: Revolutionizing Data Management and Analytics

Has it ever occurred to you that the volume of data your business processes daily is too overwhelming? You are not alone. So many companies need help in managing and analyzing enterprise data efficiently.

Introducing Snowflake Horizon, the game-changing solution that will revolutionize data management and analysis. In this blog post, I will walk you through its key features and benefits compared to other solutions.

What is Snowflake Horizon?

Snowflake Horizon is a modern data cloud solution that makes it easier for you to govern your data and enhance analytics capabilities. It is supported by the solid infrastructure of Snowflake’s Data Cloud, thus assuring scalability, efficiency, and simplicity.

Scope of Snowflake Horizon

Horizon extends beyond managing Snowflake tables and views inside your account’s internal storage. It covers a range of content, including the following:

• Data, applications, and models across your enterprise.
• Manage your data from both Iceberg tables and external tables.
• You can also share your data through private listings by trusted partners.
• Publicly available data and every Snowflake Native App from the Snowflake Marketplace
• You can migrate your data from third-party tools into Snowflake using Connectors.

Key Features of Snowflake Horizon

1. Compliance
   • Data Quality: Assures that your data meets the required threshold of accuracy and reliability.
2. Security
   • Tag-Based Masking: Masks sensitive data using tags against predefined policies you set.
   • RBAC—Role-Based Access Control: Controls access to the data based on user roles, increasing security.
   • Trust Centre: This provides you with tools and other forms of support to retain and verify trust in the framework of data governance processes.
3. Privacy
   • Projection Policy: Establish your data’s management and protection policies, ensuring compliance with privacy laws. 
4. Interoperability
   • Iceberg: Handles the management of governance of iceberg tables, therefore interoperability with your other systems. 
5. Access
   • Search: It enables data searching over the platform. 
   • Tagging: You can organize your data by adding tags. 
   • Classification: Classify the data to have it correctly managed and access-controlled. 
   • Collaboration: Helps collaboration among your teams within the organization.

These would be considered Horizon’s 5 pillars, all of which combine to ensure that it provides robust data governance, security, privacy, interoperability, and accessible data management.

Who should use Snowflake Horizon?

Horizon best suits your organization if you are centered on governance, discovery, and actions concerning content.

• Data Stewards: If you want to grant access to data, applications, and models while protecting sensitive pieces, Horizon shines in content governance. It lets you protect your data as granularly as required, track its security and quality, handle sensitive data flows, and audit secure access properly.
• Data Teams: Want to spend less time searching for the right data, app, or model? Horizon makes quick content searching easier. It engages distributed locations in collaboration, where users can find data quickly, understand and trust it to extract maximum value, and take action quickly.

In essence, it eases your work and makes it efficient.

Getting started with Snowflake Horizon

Setting Up Horizon

1. Setup Roles and Permissions:

• Create roles such as `HRZN_DATA_ENGINEER`, `HRZN_DATA_GOVERNOR`, `HRZN_DATA_USER`, and `HRZN_IT_ADMIN`.
• Assign these roles to users and grant appropriate permissions.

USE ROLE SECURITYADMIN;

CREATE OR REPLACE ROLE HRZN_DATA_ENGINEER;
CREATE OR REPLACE ROLE HRZN_DATA_GOVERNOR;
CREATE OR REPLACE ROLE HRZN_DATA_USER;
CREATE OR REPLACE ROLE HRZN_IT_ADMIN;

GRANT ROLE HRZN_DATA_ENGINEER TO ROLE SYSADMIN;
GRANT ROLE HRZN_DATA_GOVERNOR TO ROLE SYSADMIN;
GRANT ROLE HRZN_DATA_USER TO ROLE SYSADMIN;
GRANT ROLE HRZN_IT_ADMIN TO ROLE SYSADMIN;

SET MY_USER_ID = CURRENT_USER();
GRANT ROLE HRZN_DATA_ENGINEER TO USER identifier($MY_USER_ID);
GRANT ROLE HRZN_DATA_GOVERNOR TO USER identifier($MY_USER_ID);
GRANT ROLE HRZN_DATA_USER TO USER identifier($MY_USER_ID);
GRANT ROLE HRZN_IT_ADMIN TO USER identifier($MY_USER_ID);

2. Setup Warehouse and Database:

• Create a warehouse and assign usage to roles.
• Create a database and schemas, and grant necessary permissions.

USE ROLE SYSADMIN;

CREATE OR REPLACE WAREHOUSE HRZN_WH WITH WAREHOUSE_SIZE='X-SMALL';

GRANT USAGE ON WAREHOUSE HRZN_WH TO ROLE HRZN_DATA_ENGINEER;
GRANT USAGE ON WAREHOUSE HRZN_WH TO ROLE HRZN_DATA_GOVERNOR;
GRANT USAGE ON WAREHOUSE HRZN_WH TO ROLE HRZN_DATA_USER;
GRANT USAGE ON WAREHOUSE HRZN_WH TO ROLE HRZN_IT_ADMIN;

CREATE OR REPLACE DATABASE HRZN_DB;
CREATE OR REPLACE SCHEMA HRZN_DB.HRZN_SCH;

Using Horizon for Data Quality Monitoring

1. Ingest Data:

• Use structured, semi-structured, and unstructured data with real-time and batch ingestion.
• Apply Data Quality (DQ) rules and profiling.

-- Ingest data command example
COPY INTO HRZN_DB.HRZN_SCH.YOUR_TABLE
FROM 's3://your-bucket/your-path'
FILE_FORMAT = (TYPE = 'CSV');

2. Identify and Remediate Issues:

• View and remediate data quality issues.
• Monitor sensitive data and ensure it meets quality standards.

-- View data quality issues
SELECT * FROM HRZN_DB.HRZN_SCH.YOUR_TABLE WHERE DQ_FLAG = 'ISSUE';  
-- Remediate issues
UPDATE HRZN_DB.HRZN_SCH.YOUR_TABLE SET COLUMN = 'NEW_VALUE' WHERE DQ_FLAG = 'ISSUE';

Using Horizon for Data Governance

1. Monitor Data:

• Data governors can view and remediate data quality issues and monitor sensitive data.

-- Monitor sensitive data
SELECT * FROM HRZN_DB.TAG_SCHEMA.ROW_POLICY_MAP WHERE role = 'HRZN_DATA_GOVERNOR';

2. Automated Recommendations:

• Share and use data with automated recommendations to ensure proper governance.

-- Automated recommendations
CALL SYSTEM$RECOMMEND_TAGS('HRZN_DB.HRZN_SCH.YOUR_TABLE');

Using Horizon for Access & Audit

1. Analyze Access:

• Security administrators can analyze access and roles to ensure data is used securely.

-- Analyze access
SELECT * FROM SNOWFLAKE.ACCOUNT_USAGE.ACCESS_HISTORY WHERE ROLE_NAME = 'HRZN_DATA_USER';

2. Analyze Roles:

• Ensure roles have appropriate permissions and no access abuses occur.

-- Analyze roles
SHOW GRANTS TO ROLE HRZN_DATA_USER;

You can refer to the Snowflake Horizon Quickstart Guide for more detailed steps and examples.

Benefits of Snowflake Horizon

Horizon has numerous benefits that can significantly improve how your business works. 

• Improved Data Management: Effective data management is the prime factor in any business. Horizon smoothens out all of your data processes when you want your data to be properly accurate and consistent.

• Better Analytics Performance: Get more power in advanced analytics to deliver more profound insights into data-driven decisions. Horizon enables highly sophisticated analytics, helping its users discover hidden processes and trends in data.

• Scalability and Efficiency: Horizon scales seamlessly with your business, whether you have terabytes or petabytes of data. It can do anything without compromising performance.

Use Cases

Use Case 1: A pharmaceutical company

Challenge: The company relies on vast data to operate. This data includes everything from product formulas and clinical trial results to customer information and financial records. However, it faces several challenges in managing this data, such as strong regulations, data quality concerns, and siloed information hindering data-driven decision-making.

Solution: The company leverages Snowflake Horizon to establish robust data governance and empower users with seamless data discovery.

1. Governing Content: The company prioritizes regulatory compliance and data accuracy. Snowflake Horizon empowers with:
   • Compliance Certifications: Built-in certifications ensure adherence to industry regulations (HIPAA, GDPR, etc.).
   • Encryption & Authentication: Multi-factor authentication strengthens access control.
   • Data Masking: Sensitive patient information can be masked for authorized users with lower access privileges.

2. Discovering and Taking Action on Content: Researchers need to access clinical trial data from various departments. Horizon streamlines knowledge sharing:
   • Universal Search: Researchers leverage natural language search to locate relevant data across databases, tables, and views.
   • Data & App Sharing: Secure data sharing allows project collaboration while maintaining governance policies.
   • Data Lineage: Horizon facilitates tracing the origin and transformation of data sets, ensuring data provenance for reliable analysis.

Use Case 2: A financial services firm

Challenge: A large financial services firm manages a massive 10 PB of data. Ensuring compliance, data quality, and user access across this vast information is critical for informed decision-making.

Solution: The firm leverages Snowflake Horizon to effectively govern and discover its data content.

1. Governing Content: The company prioritizes data-driven decisions. Horizon empowers the data steward to monitor data quality through:

• System-defined & Custom Metrics: These metrics provide continuous insights into data health.
• Automated Scheduling: Regular data quality checks ensure consistency.
• Identify Network Policy Gaps: The built-in interface helps pinpoint missing network policies, safeguarding the account from unauthorized access.

2. Discovering and Taking Action on Content: An analyst requires product performance data for a new dashboard. Horizon simplifies this process:

• Internal Marketplace: The analyst locates the relevant organizational listing containing performance data published by the finance team.
• Data Dictionary & Querying: Data previews within the Data Dictionary allow for easy exploration. The analyst leverages the Unified Listing Locator to query the data for their dashboard seamlessly.
• Universal Search: Utilizing natural language search, you can search for a relevant data product from the Snowflake Marketplace that can be joined with the existing product performance data.

Comparative Analysis

Let us evaluate Horizon, Redshift Serverless, and BigQuery Omni against key parameters. We will help you choose the best cloud data warehousing solution available.

Each tool has its unique data management benefits:

• Snowflake Horizon’s strengths are its comprehensive governance and security features, making it useful for your organization looking to have precise control over its data.
• Amazon Redshift Serverless stands out with its built-in high performance and flexible pricing.
• Google BigQuery Omni includes multi-cloud supportability and serverless architecture, which would suit your organizations with varied cloud environments and unpredictable workloads.

Conclusion

Snowflake Horizon will revolutionize the way we manage and analyze data. With its all-inclusive innovative features, high scalability, and improved analytics capabilities, this will be an ideal solution for any business looking to stay ahead in the data-driven world.

Future Outlook

Next, Snowflake Horizon will release more advanced functionality further to deepen its leadership regarding data management and analytics.

Get in touch with a solutions expert at Hevo Data to migrate your data into Snowflake in just minutes.

Frequently Asked Questions

1. Is Snowflake built on Azure?

Snowflake is a cloud data platform that operates on multiple cloud providers, including Microsoft Azure. It is also available on AWS and Google Cloud Platform, offering flexibility to choose the cloud environment that best fits your needs.

2. Is Snowflake just a data warehouse?

Snowflake is more than just a data warehouse. It’s a cloud data platform designed for data warehousing, data lakes, data engineering, data science, and data application development. It offers data sharing, real-time data processing, and support for various workloads.

3. Why choose Snowflake over Azure?

Choosing Snowflake over Azure might depend on your specific requirements:

• Ease of Use
• Separation of Storage and Compute
• Cross-Cloud Compatibility

4. Why is Snowflake better than AWS?

• Optimized for Data Warehousing: Snowflake is explicitly designed for data warehousing and analytics, offering out-of-the-box features and optimizations.
• Concurrency Handling: Snowflake’s architecture supports high levels of concurrent queries without performance degradation.
• Automatic Scaling and Performance: Snowflake automatically manages scaling and performance, reducing the need for manual tuning and configuration.