Data Governance is growing essential. Today, companies face pressure to comply with numerous regulations, like the GDPR, HIPAA, SOX, and CCPA. However, architectural needs further complicate their ability to comply. Data growth, shrinking talent pool, data silos – legacy & modern, hybrid & cloud, and multiple tools – add to their challenges.
According to Gartner, “Through 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.”
Organizations are trying to balance dual objectives of risk mitigation and rapid growth. Hence, they are pursuing cloud transformation to help manage growth in data and cost.
Alation and Snowflake are tightly integrated, bringing robust governance capabilities to the Snowflake Data Cloud.
The Snowflake Data Cloud is one unified environment where organizations can bring different workloads together in a secure, governed manner. When it comes to enterprise governance, many are leveraging a combination of the Alation Data Catalog and Snowflake Data Cloud.
People are Overwhelmed by Too Much Data, with No Means to Govern It at Scale
Data stewards are challenged by an ever-increasing volume of data. They often lack guidance into how to prioritize curation and data documentation efforts. Oftentimes, data stewards are challenged with where to start, what to prioritize, and what’s in scope.
“The combination of Alation’s Active Data Governance, and Snowflake’s Data Cloud is game-changing. It provides a trusted view of our most important business metrics allowing our executives to use data to take immediate and confident action. This results in reduced risk, improved financial health, and greater business agility,” said Anthony Seraphim, Vice President of Data Governance, Texas Mutual Insurance Company.
Meanwhile, data scientists and analysts need access to data. They spend hours searching for data and once located, they often have to wait for IT admins to provide the right access. Once access is granted, they spend time ensuring the data is fit for purpose. They need to be able to make faster, better informed decisions with ease.
Alation and Snowflake Help You Scale Governance
Alation and Snowflake help meet the challenges of data stewards, scientists, and analysts. Our tight integration addresses the following challenges:
- Enforcing consistent data policies across a vast data landscape is difficult
- Protecting sensitive data is hard to scale
- Gaining transparency into the data lifecycle is difficult
- People lack confidence in data due to lack of context
Read on to learn how together Alation and Snowflake address these challenges and empower people with great data everywhere in the enterprise.
The Challenge: Enforcing consistent data policies across a vast data landscape is difficult
Traditionally, stewards spend hours enforcing the right policies with little to no certainty they have implemented everything comprehensively. They’ve carried the burden of employee compliance, taking all the responsiblity for curating and describing data so that others can understand and use it.
Physical compliance is the other side of the equation. Snowflake provides great physical security and governance through the use of features, such as content-based row access policies, masking policies, and tagging. But physical security is only part of what is needed.
So how do you guide employee compliance? How do you relieve stewards of this burden? Compliance includes defining policies for usage, access, sharing, and privacy. In other words, how do you know what data to secure? When do you secure it? For whom, and for how long? The Alation data catalog provides these capabilities so you maintain the correct Snowflakes configuration.
The Solution: Data masking & row access policies accelerate data access by applying consistent privacy policies
Alation provides a single pane of glass for all Snowflake data and the policies at play. The Alation Policy Center lets data stewards manage data governance policies in Snowflake from within the Alation platform. All Snowflake policies, such as row access and data masking, that are enunciated in Snowflake, are automatically extracted & ingested into Alation and centralized into one location – making it much easier to discover and apply policies.
“Alation and Snowflake’s integration empowers Texas Mutual Insurance to be more data-driven and will improve our policy process,” said Anthony Seraphim, Vice President of Data Governance, Texas Mutual Insurance Company. “In the future, our data team will centrally manage and audit Snowflake data policies in Alation, ensuring that data is protected. It’s a critical component as we use data to develop better products and services for our customers and keep private data protected.”
Alation Policy Center empowers data stewards to govern Snowflake data.
Stewards can further use Alation’s SQL query writing interface, Compose, to create new data policies easily. A key feature of Compose, SmartSuggest, automatically surfaces meta-information gathered from your peers to help make your queries more powerful. People can also save queries for reuse, and build on the work of their peers. This enables stewards to create policies with ease.
The Challenge: Protecting sensitive data can be hard to scale
Organizations need to ensure that data use adheres to policies (both organizational and regulatory). In an ideal world, you should get compliance guidance before and as you use the data in the Data Cloud.
In-workflow guidance should leverage the intelligence of your organization. Imagine writing a SQL query or using a BI dashboard with flags & warnings on compliance best practice within your natural workflow. Automation like this will help organizations comply – while enabling data scientists and analysts to make decisions quickly.
The Solution: Object tagging helps you meet regulatory requirements at scale by protecting sensitive data
Alation’s Analytics Stewardship enables data stewards to prioritize data based on importance. Stewards are able to apply policies and documentation in bulk to meet growing demands. Through features like agile approval, Analytics Stewardship facilitates direct communication of policies to data scientists and analysts within their day-to-day workflow.
The catalog automatically suggests new business glossary terms using AI/ML and links those terms to relevant data, saving valuable time and effort for stewards.
The Stewardship Workbench lets stewards track curation progress.
Alation provides deep integration with the Snowflake Data Cloud. The catalog marries business-level metadata with data governance information from Snowflake (object tagging). This makes the life of a steward simpler as they now easily know and control data by applying business context.
The Challenge: Gaining transparency into the data lifecycle is difficult
For regulatory reasons, data stewards need a complete picture of sensitive data. They need to know where it’s coming from, as well as how and where it is being used. An ideal platform should provide lineage: A deep mapping of the dependencies all the way from source to target.
Data scientists and analysts need to trust that data. As a data user, you need the confidence that the data is accurate before you use it. You need to know whether the upstream source is reliable. You need an understanding of the processes that transformed the data, from the source to the target.
The Solution: Improve data usage by providing transparency into the data lifecycle with object dependencies
A tight integration provides a complete picture of sensitive data. Alation has an out of the box analysis of Snowflake lineage (object dependencies). Alation provides a holistic view of data lineage, both upstream and downstream, which enables impact analysis of the Snowflake Data Cloud and beyond. This impact analysis of downstream objects and upstream dependencies provides data stewards a deeper understanding of how and where sensitive data is used.
Run impact analysis on your Snowflake cloud data in Alation.
By surfacing warnings to data scientists and analysts in their workflow, Alation’s impact analysis helps them gain confidence in data. That is, if the upstream object has been deprecated then Alation can push the warning to the user in real-time.
The Challenge: People lack confidence in data due to lack of context
Data stewards have limited time to govern and curate data. They find it difficult to know where to focus their effort. Ideally, they should focus on data of maximum value.
Typically, they rely on surveys gathered through tribal knowledge. That is, they collected information, in most cases anecdotal, from data users and IT admins about the data and data sources. This is a very siloed way of getting intelligence! The dependency on people makes these surveys susceptible to errors and incompleteness. You need a platform that can connect to all the data and provide visibility (access history) into the data and how it is being used.
Most often data scientists and analysts have questions about the data. They need to know who the expert of the data is. Furthermore, they should be able to identify complementary datasets that help speed up analysis. They also need to know what filters and transformations can be applied while using this data.
The Solution: Access history lets you deliver trusted data alongside visibility to accelerate everyone’s productivity
Alation learns from human behavior around data in order to support and improve it. The platform uses a Behavioral Analysis Engine to examine query logs and understand how data is being used. By ingesting all the access history of the data, Alation augments the data with business context.
The data that is most used is likely the most useful. Alation automatically gathers usage insights to identify this data and spotlight the data assets that are related and most relevant. Then it runs a Machine Learning algorithm to find the popularity.
Knowing what’s popular is powerful. By combining insights into the popularity of data sets along with their level of curation, Alation shows data stewards exactly where they should focus their efforts. This usage information also informs search rankings, making what’s most valuable most visible to the wider organization.
Users can sort data into domains and explore data assets by popularity.
By tracking data usage, Alation identifies subject matter experts. Automated expert identification pinpoints ideal stewards and makes it easy to ask questions of the right person every time. The result: business users, data scientists and analysts can see who the experts are for any given data asset. They easily ask the expert a question through built-in conversation capabilities and converse with that person on a single platform.
Recommandations, too, are embedded in the platform. Alation helps people while querying or creating a report by offering meaningful recommendations for joining multiple tables and columns. Plus, they can select the most relevant data by applying the recommended filter – saving time and effort for everyone.
It’s finally possible to reduce risk and accelerate productivity. The Alation Data Governance and Snowflake Data Cloud provide a comprehensive solution that satisfies dual objectives of mitigating compliance risk and accelerating productivity. Organizations using Alation and Snowflake can increase user productivity and improve data usage by delivering trust in data and transparency into the data lifecycle. Through a deep integration, this offering helps organizations meet regulatory requirements at scale. It empowers people to use data fearlessly and learn from key experts who finally get the recognition they deserve.
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