In modern days, data analysis is a common denominator regardless of the number of people in an organization. The data analytics in your organization should be able to leverage all your essential data through data science or BI initiatives. Snowflake partner enables you to take advantage of your data while ensuring faster and more secure data analysis. The following post will provide you with a simple guide to snowflake partners.
By connecting to Business Intelligence & Analytics service powered by snowflake partner, you will remove all the possible barriers and other time-consuming processes, such as signing in to a new partner application and manual configurations. This ensures a robust and quick transformation of data and analysis in the snowflake ecosystem. The following are some of the essential steps to guide you on snowflake partner-
- Create a Snowflake account if you do not have one.
- After creating a secure account, you should select a partner from the list. For example, you can select either Fivertran, Stitch, or Alooma.
- Take your time to review the partner you have selected. Learn how it works and the basic information about it. If you’re satisfied and feel it will fulfill your needs, click connect.
- You’ll receive a notification that your account has been created successfully; you should click on the launch button, where you will be redirected to the partner sites in the new tab.
- You can now link your partner account with your snowflake account.
- Finally, you should use the partner application to link to your existing data sources and start loading new data.
Your snowflake partner should have three basic layers that are independent and scalable, which include;
All data you load on your snowflake account are stored in the data storage layer, including structured and semi-structured data. Snowflake will automatically organize and manage your data depending on its size, composition, structure, statistics, and metadata. The data storage layer works independently.
Therefore, for easy and quick data analysis, your snowflake account should have a data storage layer that is effective and accurate.
The virtual warehouse is found in the compute layer, responsible for executing data processing tasks required for review. The virtual warehouse also works independently without interfering with the data storage layer or other computing resources. However, the compute layer can access all the data in the storage layer for inquiries. The compute and storage layer’s independent functioning ensures no disruption or competition of resources while the queries are running. Hence, there is no need to rebalance or redistribute the storage layer’s data.
With the cloud services layer, you will eliminate the tedious task of manual data management. The cloud services are responsible for data authentication, infrastructure management, access control, query parsing and optimization, and metadata management.
Benefits of Snowflake Partner
With a snowflake partner, your organization will benefit in various ways, such as;
High Performance and Speed in Data Analysis
With a compute layer, you can load and analyse data faster and deal with a large volume of queries with less time. With the virtual warehouse, you can maximize the use of the available compute resources to scale up your data.
Management of Structured and Semi structured Data
You can load your data into the cloud database without sorting them out or transforming them. The storage layer will automatically analyse the data and how they should be stored and queried.
No Concurrency in Data Computation
With Snowflake, you will be able to deal with concurrency issues. The snowflakes layers work independently without competing for computing resources which means that queries from one virtual warehouse will not interfere with questions from another.
Easy Data sharing
With Snowflake, you can share data among your data consumers while being guaranteed security.
Snowflake has compelling features that ensure the security of your data. Communications to all networks are encrypted.
When creating a snowflake partner, you need to consider integrating all the primary workloads such as data science, data engineering, Data Lake, data, and data application. These workloads ensure that your Snowflake is very effective and competitive. In addition, you need to design a snowflake partner that is consistent with your organization’s official brand.
This helps to avoid confusion among your users. Further, you need to create simple snowflake partner content that all your users can easily use and meets the organization’s needs. Using the above simple guidelines, you can create an effective snowflake partner for your organization regardless of the number of users.