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Building a Data Platform on Snowflake

Business Intelligence & Insights
Cloud Infrastructure Modernization
Platform Management
Snowflake
01 Aug 2024
5 min read

Ed Coronado

Snowflake provides a centralized data management platform to help eliminate data silos, improve data accessibility, and simplify data managements tasks. In addition, it offers a foundation to improve data quality, enhance data analysis and insights, and spur data-driven decision-making while also benefiting your company with cost savings, operational efficiency, and scalability for future growth. In addition, moving to Snowflake can help set you on a course to gain a competitive advantage in today’s data-driven marketplace.

Let’s explore the key benefits of using the Snowflake data platform, walk through the steps to build one, and explore additional tips to consider for effective implementation.

Key benefits of the Snowflake data platform

There are a variety of reasons why you may consider adopting Snowflake’s data platform for your data needs:

Separation of storage and compute: Snowflake’s unique architecture decouples storage and compute resources, allowing you the ability to scale each independently. This can improve cost efficiency, as you only pay for the resources you use. Plus, you can scale resources up and down quickly to meet changing needs.
Ease of use: Snowflake is designed for simplicity and ease of use. By requiring minimal setup and maintenance, you can focus on deriving insights from your data. You can also scale seamlessly to handle massive amounts of data and concurrent users without performance degradation.
Cloud-native and multi-cloud support: As a fully managed cloud data platform, Snowflake eliminates the need for on-premises infrastructure and its associated costs. By accessing multi-cloud support, you gain the flexibility to choose the cloud provider that best suits your needs or adapt a multi-cloud strategy.
Data sharing and collaboration: Snowflake’s secure data sharing capabilities allow you to seamlessly share live, governed data with partners, customers, or other internal teams. This fosters collaboration, assists in de-siloing the business, and enables data-driven decision-making.
Robust security and governance: Snowflake provides robust security features, including data encryption, access control, and auditing capabilities. It also supports data governance initiatives to help you maintain internal and regulatory compliance and protect sensitive information.

How to build a data platform on Snowflake

Below is a series of well-defined steps involved in building a data platform on Snowflake:

Define goals and objectives: Clearly outline the purpose of your data platform (e.g., analytics, reporting, data science). Identify the key stakeholders and their requirements. Determine the scope of the project, including data sources, data types, and expected outcomes.
Design the architecture: Choose a Snowflake edition (standard, enterprise, business critical) based on your needs. Design the data warehouse schema, including tables, views, and relationships. Decide on a data loading strategy (batch, streaming, or a combination). Consider data security and access control measures.
Set up your Snowflake environment: Create a Snowflake account and configure it according to your organization’s policies. Set up storage integrations for your data sources (e.g., Amazon S3, Azure Blob Storage). Create virtual warehouses for data processing. Define roles and permissions for users and groups.
Load data: Extract data from source systems (databases, files, APIs). Transform the data to match the Snowflake schema (if necessary). Load the data into Snowflake using Snowpipe, COPY INTO, or other methods. Schedule data loading to keep the data warehouse up to date.
Transform and model data: Use Snowflake’s SQL capabilities to transform and model data. Create views, materialized views, and stored procedures for data aggregation and analysis. Implement data quality checks and validation rules.
Build analytics and reporting: Connect Snowflake to your preferred BI or analytics tool (e.g., Looker, Power BI, Amazon QuickSight). Create dashboards, reports, and visualizations to gain insights from your data. Set up alerts and notifications for important metrics.
Optimize performance: Monitor query performance and optimize as needed. Use Snowflake’s clustering and partitioning features to improve performance. Consider using Snowflake’s materialized views for faster query response times.
Maintain and govern: Regularly monitor data quality and address any issues. Implement a data governance framework to ensure data accuracy, consistency, and security. Update the data platform as business needs evolve.

Additional tips for Snowflake implementation

When building a data platform on Snowflake, there are few other considerations that can enhance your implementation and optimize performance. These tips will help ensure a smoother deployment and maximize the benefits of Snowflake’s capabilities for your organization.

Start small: Begin with a pilot project to test the Snowflake environment and your data pipelines.
Leverage Snowflake documentation: Refer to Snowflake documentation for detailed instructions and best practices.
Consider using Snowflake partners: Partner with experienced Snowflake consultants or service providers to accelerate your implementation.
Cost management: Monitor usage and costs and adjust resource allocations as needed to optimize spending.
Backup and recovery: Implement backup and recovery strategies to safeguard data and ensure business continuity.
Training programs: Conduct training sessions for users to ensure they are proficient in using the Snowflake platform. Upskill your internal team.
Documentation: Maintain comprehensive documentation covering all aspects of the data platform, including architecture, data models, processes, and policies.
Feedback loop: Establish a feedback loop with stakeholders to continuously gather input and make improvements.

Next steps in building a data platform

The Snowflake data platform offers a transformative solution for organizations aiming to enhance their data management and analytics capabilities. By adopting the best practices discussed, you can tap into its full potential and drive impactful business outcomes.

If you’re looking to navigate the complexities of implementation and optimize your use of Snowflake, Wavicle is here to assist. Reach out to us today to learn how our expertise can help you build a successful data platform tailored to your needs.

WIT Leader

Ed Coronado

Ed brings 25+ years of experience building cloud and data platforms across Snowflake, Azure, AWS, and Databricks. He leads Wavicle’s tech COE with deep architecture and solution design expertise.

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Building a Data Platform on Snowflake

Ed Coronado

Key benefits of the Snowflake data platform

How to build a data platform on Snowflake

Additional tips for Snowflake implementation

Next steps in building a data platform

WIT Leader

Ed Coronado

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