Snowflake Clean Room: Future of Cross-Cloud Data Collaboration

Snowflake Clean Room is discussed extensively in this blog. It covers topics such as Snowflake Clean Room Factors, Use-Cases, Benefits, and How to Set Up a Snowflake Clean Room. It also includes a brief introduction to Snowflake and the Data Clean Room.

Snowflake is a data warehouse that operates on a cloud infrastructure. It is designed to use an advanced SQL database engine with a distinctive cloud pattern. Its eminence relies on its capability of scaling storage and computing independently, so the customers can control cost expenditures accordingly. It isn’t supported by private cloud or hosted infrastructures. Snowflake automatically administers all parts of the data storage process, including organization, structure, metadata, file size, compression, and statistics. It is available on Azure and AWS cloud platforms.

Table of Contents

• What is Snowflake?
  • Key Features of Snowflake
• What is Data Clean Room?
• How does a Data Clean Room work?
• What are the Use Cases of Data Clean Room?
• What is Snowflake Data Clean Room?
• Factors that Snowflake Clean Room Must Control
• What are the Use cases of Snowflake Data Clean Room?
• What are the Benefits of Snowflake Data Clean Room?
• How to Setting up a Snowflake Data Clean Room?
• Conclusion

What is Snowflake?

Snowflake is a fully relational,  SQL-based Cloud Data Warehouse that offers a Database as a Service (DBaaS) platform to users. Snowflake can give your business the flexibility and agility required to meet the changing data needs. Its flexible Cloud Storage allows you to store almost unlimited amounts of structured and semi-structured data in one location thus consolidating the data from your various data sources. Moreover, this virtual Data Warehouse is scalable and enables your business to meet growing data needs without additional purchases or overheads

Key Features of Snowflake 

Caching Results: A remarkable feature of the snowflake is caching results at various levels. This means after a query is executed, the data result stays still for 24 hours. So if the same query is carried out again, by any user within the account; results are already available. This is beneficial when you want to compare a query before and after an alteration.

Unique Architecture: A fusion of both traditional shared disk and shared-nothing database. Akin to shared-disk architecture, snowflakes draws on a central repository for the data that is accessible from all nodes in a platform. On the other hand, it operates using MPP (massively parallel processing) compute clusters where every node stores some of the entire data individually. just like a shared-nothing database. so that users can enjoy the simplicity of the shared-disk architecture and the performance and benefits of a shared-nothing database.

Data sharing: Snowflake is offering a secure data sharing feature that enables object sharing from a database of one account to another without creating a duplicate. this ensures more storage space and fewer storage expenditures. snowflakes metadata store makes it easier and quicker.’ to access the data. Hence snowflakes create a network of data providers and consumers that allows for many use cases. for those who don’t hold an account, snowflake provides an option to create a readers account, a cost-effective way that enables consumers to access the shared data for free.

Handling Semi-structured data: To handle semi-structured data, Snowflake’s architecture employs a schema on reading data type called VARIANT.it stores both structured and semi-structured data in the same destination. Once the data is loaded snowflake automatically extracts the attributes by parsing the data. Later this data is stored in columnar format.

Least administration: Delivered as Data Warehouse as a service, Snowflake employs minimum administration. The scalability feature allows the least involvement from DBA and IT teams. There is no need to install software or hardware.

Scalability: Snowflake’s architecture independently scales the compute and storage resources. This allows users to scale up resources when a large amount of data has to be uploaded in a short interval of time and scale back down when done, without any intrusion to service. To minimize administration, snowflake has instilled auto-scaling. this makes an automatic start and ceases of the clusters during unpredictable resource processing.

Retrieving Objects: To make mistakes is human. the UNDROP command is the solution to the mistakes we make while sharing the data by dropping the wrong table. recovering the data traditionally can cost you a lot of time restoring and backing up. Using this command snowflake enables you to recover the data instantly as long as you are in the recovery window.

Zero copy clones: If you want to clone an already existing database, Employing traditional data warehouse services is hectic as you have to deploy a totally new environment and upload the data. This isn’t feasible because it can cost an extra amount to the customer. Snowflake’s zero-copy feature is the solution to this problem. Using this feature you can instantly clone without creating a new copy that saves up your storage.it alters the clone on its metadata store while in the back end still referring to the original data file. Its time-traveling feature, to make clones of the data from some past point in time makes it one of the best warehouses.

What is Data Clean Room?

A Data Clean Room is a secure, protected environment where PII (Personally Identifiable Information) data is anonymized, processed, and stored in a privacy-compliant manner before being used for measurement or data transformations. The raw PII is provided to the brand and can only be viewed by the brand.

How does a Data Clean Room work?

All user-level first-party data is loaded into this secure environment from CRM systems (including historical data), such as Salesforce, or ecommerce platforms (such as Shopify, Magento, and Epsilon). Other data sources, such as historical and current transaction data, can be made available in the cleanroom environment for a variety of applications.

The PII data sent to the cleanroom is hashed before transmission, and it is secured and encrypted once it enters the cleanroom, preventing unauthorized access. Partners can get a feed with hashed PII data as an output, while brands have full control over the cleanroom. This anonymized data can then be shared with measurement partners like

What are the Use Cases of Data Clean Room?

• User-level PII data that can be used for measurement is anonymized.
• Uploading offline data to publishers like Facebook for match-back processes can be automated.
• Customer analysis at the user level, including LTV reporting and cohort level analysis
• Built-in support for privacy regulations such as the CCPA, CPRA, and GDPR.

What is Snowflake Clean Room?

The Snowflake Clean Room is a secure place for different companies or different branches of a single company to analyze data together without violating privacy laws under defined restrictions and guidelines.

These guidelines align the data usage with privacy laws such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Personally identifiable information (PII) is incognito, processed, and stored in a compliant way within data clean rooms. Having so many concerns regarding security in the marketing world people are getting more interested in the concept of data clean rooms.

Snowflake Clean Room allows rapid sharing of data while keeping personal information anonymous. In order to achieve desired business progress, you can identify high-value targets, regressed customer rates, and other opportunities for your business.it is a platform for joined analysis of sensitive data while following rules and regulations.it can be set by anybody but mostly it’s the provider.

Snowflake Clean Room work by keeping the privacy environment alive.no information that could be tied back to a specific user is not allowed thus enabling better targeting.

Factors That Snowflake Clean Room Must Control

The factors Snowflake Clean Room must control:

• What sort of data is entering the room
• In the cleanroom how the data can be joined to other data
• What types of analytics each party is capable of performing on the data
• What sort of data can leave the room.

What are the Use Cases of Snowflake Clean Room?

Audience Insights For an Advertisement

If a company has its first-party data consisting of the qualities about its customers and associated sales stock keeping unit” (SKUs). That being the case, the company can employ the Snowflake Clean Room feature to improve the insights of the audience for the advertisement. Let’s assume that the company is looking for new customers with the same qualities as its best customers and to amalgamate those qualities with other characteristics to excel upsell opportunities.

Monetizing Proprietary Data

The omnichannel customer journey is multiplex and rarely starts with a brand’s advertisement. For instance, A consumer is making plans for a forthcoming purchase of a home appliance. He will start his journey most likely with online available review sites. Review sites collect top-of-funnel data that is useful to appliance brands. So the site can create a third-party data product with a data clean room that manages personally identifiable information (PII).

CPG-Retail Collaboration

retailers and consumer packaged goods (CPG) companies use data clean rooms for collaboration with other brands most likely those advertising with them. Let’s take an example where a retailer shares his transaction data in a governance-free manner that provides conversion signal insights and enables better target achievement, and personalized attribution. If you get to know that your products are selling after the customers see your advertisement this will ensure a return on your investment of marketing dollars.

What are the Benefits of Snowflake Clean Room?

There are a variety of benefits offered by Snowflake Clean Room for advertisers, media companies, and retailers.

A secure data share complacent with guidelines

With the key traits of security and access controls of data clean room, media companies and publishers can provide comprehensive reports and advertisers can track attribution.

Building Custom Audience

The custom audience could be built using data cleanrooms. This can be useful for advertising platforms., For example, Instagram and Facebook for advertising. This allows marketers to polish up their ad targeting.

Advanced Analysis

Using data cleanroom organizations can conduct scrupulous analysis on combined data sets to get insights into the behavior of the customer, segmentation, and customer’s lifetime value.

How to Setting up Snowflake Clean Room?

You can set up your snowflake Clean Room by following these simple steps:

1. For each company, divisions of a single company, and group, buy a Snowflake account.
2. Load your data on your snowflake account.
3. Set up a snowflake Private Data Exchange among the participants.
4. Set up secure functions and joins for the protection of your data.
5. Use standard analysis tools to analyze the joint data, while following the privacy policies of each party.

Conclusion

Snowflake Clean Room is a safe place to jointly analyze data while keeping the sensitive data incognito. It is the best option for rapid data sharing while keeping your information secure and governed. Comparing data with other organizations allows seeing data sets overlap. That could be used for better targeting, personalization, and attribution Snowflake data clean rooms help publishers, retailers, and different companies to improve their add effectiveness. Anyone can set up a data clean room but mostly it is the provider.

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