In today’s data-driven world, organizations invest in their data and analytics resources to finish projects quickly and flawlessly.
As a result, data catalogs have swiftly established themselves as an important element of modern data management. Successful data catalog deployments result in significant improvements in the speed and quality of data analysis and the involvement and interest of those who must execute data analysis.
In this article, you will learn:
- What is a Data Catalog?
- Advantages of Connecting Snowflake to a Data Catalog
- Snowflake Metadata Repository
- Integrating Snowflake With a Data Catalog
- Conclusion
This is part of our Snowflake Security guide. You may find our complete data management guide useful as well.
What is a Data Catalog?
Before humans invented the internet, catalogs served as a reliable means of organizing, storing, and retrieving individual data. There were a variety of other data governance methodologies way before Data Catalogs.
However, adopting a Data Catalog in your organization is one of the greatest methods to keep your data easily accessible, structured, and safe today.
A Data Catalog is a collection of metadata paired with data management and search capabilities that assists:
- Analysts and other data consumers in locating the data they require
- Acts as an inventory of existing data sets
- It gives information to evaluate data for intended data usage
Today, organizations attempt to grasp all of the data within and outside the enterprise’s Snowflake metadata repository. A Snowflake Data Catalog enables them to observe their implementations and conduct real-time analysis to gain immediate value. Snowflake is a cloud data warehouse that allows you to store and analyze all of the enterprise data in one place.
A Snowflake metadata repository provides data storage repositories for structured data ingestion for reporting and data analysis. Snowflake’s capacity to handle mountains of unprocessed data assets from various data sources in multiple formats makes it an appealing data platform to several IT decision-makers.
Advantages of Connecting Snowflake to a Data Catalog
Below are the benefits of connecting Snowflake to a data catalog:
Search and Discovery Capabilities
The Snowflake Data Catalog includes sophisticated search tools to assist users in rapidly and easily locating data assets. Users may easily search for and obtain relevant information, making it simple to manage data.
Reduced Data Integration Costs
Having a data catalog for your Snowflake data may make processes more efficient, and reduce costs with direct and regulated access to ready-to-query data while ensuring data quality.
Quicker Access to New Data
A Snowflake Data Catalog saves the time-consuming process of copying traditional data from a business glossary and transferring it to Snowflake using the Snowflake secure data exchange technology. Moreover, it makes it easier to access live, shared, and governed data sets. Users may also receive real-time changes to the data, allowing them to trace the whole data lineage.
Data Quality Monitoring and Control
A Snowflake account has comprehensive quality check features that scan the organization’s data for duplication, formatting errors, missing values, and data usage patterns. This option is beneficial for ensuring data quality in a company.
Data Lineage
It is more simple to follow the data journey with a Snowflake Data Catalog, such as the data origin, digital transformations, and destination. This aids in tracking the changes made to data to allow impact and root cause analysis.
Snowflake Metadata Repository
You can handle data in a Snowflake metadata repository even outside the company’s Snowflake account. However, companies should keep in mind that when using Snowflake, it is their responsibility to make sure that no personal data, sensitive data, export-controlled data, or other regulated data, is inserted into any metadata field.
The following are the most frequent metadata fields:
- Object Definitions include a policy, an external function, or a view.
- Object Properties include an item name or a comment on an object.
Integrating Snowflake With a Data Catalog
Snowflake is a cloud data platform (commonly referred to as a cloud data warehouse) that delivers the speed, concurrency, and simplicity of use necessary for storing and analyzing all of a company’s data in a single location, all in the cloud.
Thanks to Snowflake’s ability to separate storage capacity from computing resources, you may dynamically increase the storage capacity of your data lake. However, this gets done without regard to the number of compute nodes present and scales your computing clusters elastically to meet demand only when necessary.
You can answer the following data questions with the help of a Snowflake Data Catalog:
- What type of data is being used by which organization?
- What is the relationship between the views and tables?
- When was the last time the data was updated?
- In a table, what are the most significant columns?
With that out of the way, you can then connect to Snowflake Data Warehouse and access data through it through the following steps:
- Click Create, then Connection, from the Home page.
- Select Snowflake Data Warehouse from the drop-down menu.
- Give your connection a name.
- Enter the host account name in Hostname in the following way: <account>.snowflakecomputing.com (where the account is the Snowflake account name that you want to use to access the data)
- Enter the login credentials for the Snowflake data source in the Username and Password fields.
- Enter the name of the database containing the schema tables and columns you want to connect to in Database Name.
- Enter the name of the warehouse that has the database, schema tables, and columns you want to connect to for Warehouse.
- Click Save.
Conclusion
A data catalog makes data management and meeting the company’s multiple objectives easier. Even more powerful, a Snowflake Data Catalog will simplify organization users to locate and comprehend Snowflake data.
Data gets generated exponentially as your business grows across all of your company’s SaaS applications, databases, and other sources. To address the expanding data storage and computing needs, you will need to devote some of your resources to integrating data from various sources, cleaning and transforming it, and finally loading it into a Cloud Data Warehouse like Snowflake for other Business Analytics.
Satori can help you simplify data access and management for Snowflake, as well as your other data platforms. Data is continuously discovered and classified by Satori without any data scan. Furthermore, you can define security policies across all your datastores, and even enable self-service access to data.