5 Snowflake Data Warehouse Benefits To Your Business

Snowflake is essentially a data warehouse built on top of Microsoft Azure cloud infrastructure or Amazon Web Services. Snowflake Data Warehouse is the hottest topic both in business and data science. It helps organizations collect more data than ever before. It is an analytic data warehouse provided as software as a service(SaaS). It is faster, easy to use, and more flexible than a traditional data warehouse.

The best part of Snowflake is there is no need for software or hardware to install, manage, or configure. Snowflake is ideal for companies that don’t want to dedicate resources to set up, support, and maintain in-house servers.

Apart from its data sharing and architecture capabilities, snowflake architecture allows storage and computation to scale independently. So that consumers can use and pay for storage and computation separately. There is a sharing functionality in the Snowflake data warehouse, which makes it easy for companies to share secure and governed data in real-time quickly.

When purchasing a cable television service during the initial days of cable TV, we used to get a package deal of infrastructure and content. But today, those things are separated. Now consumers have more power over what they use and how they pay for it.

Similarly, Snowflake architecture allows flexibility with big data. Snowflakes decouple the compute and storage functions. It allows organizations with significant storage demands but less need of CPU cycles and don’t have to pay for an integrated bundle that demands them to pay for both. It also helps companies that have fewer storage needs and more CPU cycles.

Users can scale up and down as required and pay for only those resources they use. Computation is billed on a per-second basis, and storage is billed by the number of terabytes stored per month. Snowflake architecture consists of three layers, which are storage, compute, and services. All the layers are independently scalable based on the requirements of the organization. Let’s look at all three layers more thoroughly:

1. Database Storage Layer – The database storage layer includes all the data stored in Snowflake, including structured and semi-structured data. It automatically manages all aspects of how data is stored. Some of the critical aspects are file size, compression, statistics, and metadata. The snowflake database storage layer works independently of computing resources.

2. Compute Layer – Snowflake compute layer is made of virtual warehouses that execute data processing tasks needed for queries. All the virtual warehouses in the compute layer can access all the data in the storage layer and then work separately so that warehouses do not share or compete for computing resources. This helps in automatic scaling, which means that computing resources can scale without the necessity to rebalance the data in the database storage layer while queries are running.

3. Cloud Services Layer – The cloud services layer eliminates the need for manual data warehouse management. It uses ANSI SQL and coordinates the entire system. This layer includes the following services:

Snowflake Data Warehouse is built specifically for the cloud and is designed to approach many of the problems found in older hardware-based data warehouses. Some of the issues like data transformation, limited scalability, and delays due to high query volumes are quickly addressed by Snowflake. Following are some amazing benefits of using a Snowflake data warehouse for your business:

1. Effective Data Sharing – Snowflake architecture allows seamless data sharing among Snowflake users. It also enables companies to share data with all the data consumers seamlessly. It doesn’t matter if these data consumers are Snowflake customers or not, as reader accounts can be created directly from the user interface. This unique functionality enables the provider to create and manage a Snowflake account for a customer. Snowflake allows your team to work collaboratively with external business partners and across your enterprise in real-time with its unique data-sharing features. Finally, with Snowflakes SQL functions, you can quickly and securely access data from anywhere in the world.

2. Accessibility – You could experience delays or failures(concurrency issues) with a traditional data warehouse. Snowflake addresses such issues with its unique multicluster architecture. Queries from one virtual warehouse will not affect the queries from another. Data scientists and data analysts can quickly get what they need, whenever they need, without waiting for other processing or loading tasks to complete.

3. Availability and Security – Snowflake is distributed across various availability zones on the platforms on which it runs. It runs on both Microsoft Azure and AWS platforms. Snowflake is a proven cloud-based data warehouse solution for many industries, including the federal government, healthcare, state and local agencies, security, and financial services. It has built-in protection that meets PCI DSS and SOC 2 Type II requirements with an additional level of encryption.

4. Storage and Support – Structured and semi-structured data can be combined easily with Snowflake. It helps analyze and load the data into the cloud without the need for transformation into a fixed relational schema first. Snowflake has the ability to optimize how the data is stored and queried instantly.

5. Speed and Performance – As Snowflake uses a modern cloud infrastructure, it evades many of the traditional data warehouses’ issues and improves the overall performance. The elastic nature of the cloud is that if you want to run a high volume of queries or load data quickly, you can scale up the virtual warehouse and take advantage of extra computing resources. Later you can scale down the virtual warehouse and pay only for the time you used.

You need to select the suitable cloud data platform service that meets your business needs in order to implement a Snowflake data warehouse. It offers a wide range of pricing and service options and provides documentation tutorials for first-time Snowflake customers. Check out the Snowflake getting started guide for additional information on implementation. It is easy to set up and data experts can learn the foundations in just 45-90 minutes.