Information Technology

<p style="text-align: justify;">In and of itself, data doesn&rsquo;t hold any special value. Rather, the insights that are uncovered from data analytics uncovers information and metadata about events, products, and historical facts. While that has added a lot of value to our analysis, occasionally that data could contain confidential aspects such as personally identifiable information (PII data such as social security numbers and mailing addresses), protected health information (PHI data such as health history and medical allergies), and secure fiscal data. As data engineers, it is our ethical and legal responsibility to protect that information.</p><p style="text-align: justify;">Database systems have evolved in the way they share information from traditional methods such as EDI and APIs to database views. Unlike ordinary RDBMS base tables, a view is a virtual table that&rsquo;s usually computed from the database when it is accessed. In general, sharing data via views provides an excellent route for creating dashboards, exporting datasets, integrating with ETL workflows, and supports several business cases. However, with all these methods of sharing data, the chance of data being accessible is high, as the security needs to be set up not only at the database level but also at the access level, allowing for a higher chance of a security breach.</p><p style="text-align: justify;">Snowflake not only supports view-based data sharing but has enhanced this by revolutionizing how organizations distribute and consume shared data. Unlike FTP and email, Snowflake Data Sharing is far easier to use as it provides instant access to live data and eliminates data copying. The Snowflake Built for the Cloud Architecture enables Data Sharing without any complicated ETL and setup and more importantly allows you to control security at one single place, at the data level.</p><p><img style="display: block; margin-left: auto; margin-right: auto;" src="https://kradminasset.s3.ap-south-1.amazonaws.com/ExpertViews/kirat1.jpg" alt="" width="602" height="351" />&nbsp;</p><p style="text-align: justify;">The data sharing feature of Snowflake uses its cloud data warehouse and unique multi-cluster, shared data architecture to enable live data sharing. This allows users to quickly set up and govern data shares in minutes to their data consumers, who can view and seamlessly combine it with their own data sources. Real-time secure sharing of data is ready as soon as a data provider adds to or updates data for the end consumers. There are out of the box advantages to this approach such as:</p><ul><li style="text-align: justify;">Immediate access: no transformation, data movement, loading or reconstruction is required, and data is available for immediate use.</li><li style="text-align: justify;">Live data: changes made in real-time by a data provider are immediately available to data consumers without effort. Thus, data is always current.</li><li style="text-align: justify;">Secure Managed access: a data provider can share all their data to N number of data consumers in a secure, governed manner with minimal effort. The flexibility of controlling all aspects of managed access increases the ease of use.</li><li style="text-align: justify;">No ETL management: users do not need to manage any ETL for secure data sharing capabilities and operations.</li><li style="text-align: justify;">Access Logs: Data providers can track and monitor access to Data Shares and quickly respond to the user&rsquo;s actions.</li></ul><p style="text-align: justify;">Snowflake secure data sharing is an excellent candidate where data monetization, the elimination of data silos, and the ease of data management are important criteria for business operations.</p><p style="text-align: justify;">For example, take an energy utility company that needs to demonstrate the value of their CRM by they need to show how customer retention, development, and other measures are improved to justify the cost of their software. The company can target their top customers with self-reporting metrics/dashboard capabilities that are deployed via secure data sharing, allowing for real-time access to key metrics, as well as creating unique views to meet their customers&rsquo; needs.</p><p style="text-align: justify;">Shared data exists independently and can be queried along with any other database within a Snowflake environment. Object&rsquo;s access is regulated through grants and only objects granted with access privileges are shared with other Snowflake users. No ETL is required to enable this, and Snowflake provides both a guided wizard and the ability to write SQL queries to establish data shares. This last functionality allows you to automate the grants through a third-party system with SnowSQL, further reducing the time it takes to onboard a customer and ensuring that the grants follow best practices and security protocols.</p><p style="text-align: justify;">The following high-level steps establish a secure data share:<br />1. &nbsp; &nbsp;Create an empty share as a shell<br />2. &nbsp; &nbsp;Add privileges for associated objects<br />3. &nbsp; &nbsp;Confirm share contents to make any updates<br />4. &nbsp; &nbsp;Share the database objects in the share via data consumers</p><p><img style="display: block; margin-left: auto; margin-right: auto;" src="https://kradminasset.s3.ap-south-1.amazonaws.com/ExpertViews/kirat2.jpg" alt="" width="602" height="220" />&nbsp;</p><p style="text-align: justify;">This straightforward process allows users to create a secure Data Sharehouses using the power of Snowflake&rsquo;s architecture. There is enough flexibility to share data with several organizations, sustain data concurrency, and various combinations of sharing views, tables, etc. without any ETL creation or management.</p><p style="text-align: justify;">Snowflake Sharehouses provide a strong, enterprise-grade workflow that enables users to spend less time to quickly and securely share their data with high flexibility and spend more time tapping into powerful insights to uncover the hidden potential of their datasets.</p><p style="text-align: justify;">&nbsp;</p>