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Data has been compared to many things—gold, oil, even currency. But what these comparisons often fail to capture is the true potential of data as a shared resource. Unlocking this potential empowers organizations to gain comprehensive insights and make informed decisions.
The most relevant data that businesses can leverage includes market trends, customer preferences, and strategic opportunities that may have otherwise remained hidden. When such data creates a more comprehensive view of reality, smaller businesses can compete more effectively with larger enterprises and thrive in a dynamic market landscape.
Data sharing of this nature is best suited to a data marketplace where data providers and consumers converge. Data marketplaces facilitate the exchange of data products and enable seamless collaboration and access to valuable datasets.
Partner data sharing is when businesses exchange data with each other. Efficient partner sharing occurs with a tightly integrated data marketplace that seamlessly connects systems for receiving and distributing data. However, partner data sharing often takes place via lower-level data platforms, like Snowflake. Partner organizations are developing connections and licensing norms to work together on the data they produce. Many companies are choosing Snowflake to facilitate these data exchanges.
What Is Snowflake?
Snowflake is a cloud-based data warehouse with a powerful engine for storing and processing large amounts of data. The platform offers several key features and capabilities that empower data partners to effectively share, manage, and analyze their data. Those features include:
- Allowing data providers to seamlessly share their data with partners or other customers without having to duplicate it.
- Introducing the concept of a “share” for businesses seeking to provide access to a designated database, schema, table, or view.
- Enabling data partners to acquire insights by combining external data with the internal data stored in Snowflake in real time.
- Empowering all data users to leverage performance analytics, scaling up on demand as the complexity of queries increases.
- Facilitating data sharing with multiple businesses, giving partners the ability to quickly build a web of B2B secure data sharing capabilities.
Snowflake is entirely SQL-based, making it extremely easy for data-capable operators to learn. Although SQL is a simple language to learn, Snowflake’s user interface caters to both customers with and without programming skills.
In summary, the platform is specifically designed for sharing data so your business can partner, collaborate on, and achieve new insights and market opportunities.
Snowflake Data Sharing: A How-To
Snowflake data sharing involves using a feature called Shares. Shares enable the sharing of database tables, secure views, and secure user-defined functions.
Snowflake secure views exist as a data access control feature. It enables users to create virtual representations of data tables with restricted access and highly specific permissions. Secure, user-defined functions refer to executable functions with controlled access privileges and limited permissions for enhanced security purposes.
These features allow users to securely share Snowflake databases with other Snowflake accounts. Setting up Snowflake shares requires following several prerequisite steps.
Define Your Snowflake Data Model
It is essential to define the data model before sharing data with a partner or data consumer. This process requires determining what types of data a consumer might need, whether the consumer is a human or machine. For example, a credit card company will primarily rely on numeric and datetime types (e.g. credit card numbers, transaction times), whereas a marketing company may solely focus on numeric or string-based data types (e.g. names and addresses on a mailing list).
When defining the data model, users must balance user access and analytical flexibility. Data providers face the challenge of providing users with access to the data they require. At the same time, they must maintain the flexibility to accommodate a diversity of analytical tasks.
Once you and your partner’s data consumer agree on the Snowflake data model (the way data is organized and structured in the Snowflake platform), the next step is to get the data ready to share.
Snowflake Secure Views
Security is at the foundation of partner sharing. As a Snowflake cloud user, the only way to ensure you provide the correct data to the consumer is to use Snowflake Secure Views. Secure Views protects customer data by allowing you to create and share secure, customized views of data without granting direct access to the underlying data or infrastructure. Snowflake Secure Views also prevent you from inadvertently revealing information that you should protect.
Use Snowflake’s “Create Share” Privilege
To share data with a data consumer’s Snowflake account, you must set up sharing permissions and connect the accounts. Data providers must have the Snowflake “Create Share” privilege to share data. If you do not have that privilege, ask your Snowflake administrator to grant it. You can then create the share, add objects, and add the data consumer’s account to the share.
Enable “Get Data”
Data consumers can access shared data by accepting the invitation to share data. Navigate to “Data” → “Private Sharing,” and find the share from the data provider’s Snowflake partner sharing account. The consumer must then give the database a name (e.g. Sales), select the appropriate role to grant access (e.g. Analyst), and click “Get Data” to access the shared data. Once the data consumer completes these steps, the shared data will be visible in “Data” → “Databases.”
It’s important to note that if you wish to share Snowflake data with consumers in a different region, you must enable replication of the source data to the target region.
Snowflake Partner Sharing: Benefits
Sharing data can unlock a multitude of advantages for your business across various industries and sizes. Let’s delve deeper into the specific benefits that Snowflake partner sharing can offer.
Data sharing can help companies generate revenue by leveraging valuable insights from other businesses. This monetization strategy is especially helpful for retailers that have vast amounts of data in their consumer databases and loyalty programs.
In Snowflake, data sharing enables data providers to gain access to new markets and learn about the preferences and needs of customers in different regions or industries. They can then use this data to determine market gaps, penetrate markets, and personalize product offerings.
The built-in integrations between Snowflake and other cloud services like AWS, Google Cloud, and Microsoft Azure make it simple for businesses to gather and store data from third-party data providers and various other external data sources.
Snowflake and other cloud services provide standardized protocols and APIs for native integrations, which facilitate seamless connectivity and data exchange. This enables businesses to efficiently transfer data between platforms.
Additional access to data helps companies gain a fuller picture of their customers and market, in turn enabling them to better spot market opportunities and gaps. They’re better equipped to uncover patterns, trends, and insights that provide a deeper understanding of their customers and market dynamics. They can also better identify underserved customer segments and expand into new geographical markets.
New Market Opportunities
Data sharing can foster collaboration and partnerships that lead to new products or services for new or existing markets. This is particularly true for businesses that work closely with their customers and suppliers, especially e-commerce platforms, supply chain companies, and software development firms. In these industries, external data can provide valuable insights into market trends, customer needs, and supplier performance.
Businesses can harness the supply chain as a competitive advantage by sharing data with internal and external stakeholders. Such collaborative efforts enable manufacturers to identify bottlenecks, cost variations, resource constraints, and logistics interruptions throughout the supply chain. They suddenly become aware of internal and external data sources like supplier events, product component lists, and product usage statistics. Once manufacturers are aware of the entire supply chain ecosystem, they can effectively reduce risks.
Data sharing can enhance security by enabling your business to track who accesses what data set, when, and from where. Snowflake data sharing also ensures that only authorized users can access sensitive data and quickly identifies security gaps. Secure Views provides data access controls with virtual representations of tables, so companies can have tighter control over what data is displayed and to whom.
Pros and Cons of Snowflake
This section highlights key features that make Snowflake cloud an attractive option as a cloud data warehouse solution.
Advantages of Snowflake
Snowflake stores extensive data on popular cloud platforms like Microsoft Azure, Google Cloud, and Amazon Web Services. Consequently, you don’t need to manage or maintain any physical hardware.
Snowflake automatically tunes its performance, so you don’t need to hire a data engineer to monitor it. It also handles all software updates and platform maintenance. Users can divide query tasks into segments to achieve higher data processing speed, reduce waiting time, and improve overall performance.
Snowflake’s disaster recovery capabilities ensure you can access your data even in the case of a system failure, natural disaster, or cyber attack. Snowflake protects your sensitive data with advanced security features like IP whitelisting, two-factor authentication, and AES 256 encryption.
Snowflake’s “cluster resizing” feature scales up data warehousing based on demand, ensuring optimal performance. This flexibility enables it to cater to businesses of all sizes and makes data warehousing a cost-effective solution.
Finally, Snowflake offers a simple pricing model and streamlined cost attribution, making it easy to allocate expenses to particular projects, groups, or individuals. In addition, there are no separate expenses associated with infrastructure.
Disadvantages of Snowflake
Although Snowflake offers many benefits as a premium data warehouse system, there are several disadvantages to consider. For companies that need support for structured and unstructured data, Snowflake isn’t quite there yet. It only supports semi-structured and structured data (although unstructured data support is coming in the future).
Likewise, data migration can be challenging with Snowflake, and their bulk data loading option, Snowpipe, isn’t always the best choice. For instance, Snowpipe users cannot query data for several minutes, until after it is staged. In addition, its throughput capabilities are limited.
The final challenge, for some organizations, Snowflake account structures. A Snowflake account is more like a group. Multiple people can be within one Snowflake account. Depending on how the roles and permissions are structured, it may be difficult, if not impossible, to use Snowflake Shares between two people on the same Snowflake account. This presents significant administrative challenges for some organizations and can be a non-trivial disadvantage.
Data Sharing: A New Opportunity
The comparisons of data to gold, oil, and currency are apt, but only when data sharing is enabled across an organization and its partners. Snowflake is an excellent tool for sharing that value. When data partners can easily share data, new lines of business and market opportunities can quickly reveal themselves.
Sharing data on Snowflake’s partner network requires several steps:
- Define the data model
- Use Snowflake Secure Views
- Configure permissions
- Enable customer data access
Although this process may seem extensive, it can offer you significant benefits such as revenue generation, new market opportunities, competitive advantage, and enhanced security.
Snowflake users can also benefit from features like automatic performance tuning, backup plans, and sophisticated security features. As noted above, this SQL-based system has a short learning curve, making it simple to use. It’s also a cost-effective alternative to data warehousing due to its scalability. While Snowflake has its limitations, its advantages arguably outweigh its disadvantages.
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