How To Get Started with Cloud Data Warehousing For Your Business

cloud data

Data is at the heart of businesses and in today’s ever competitive landscape, the importance of data analytics and insights cannot be overstated. With data, businesses can shape decisions, form strategies and respond quickly to changing consumer and market dynamics. The power of data is immense, and it all comes down to how well a business can utilise data to turn it into a goldmine for profitability and success.

To make the most of business and user data, companies have been relying on storing, managing and extracting data since decades. With the applications of databases and application systems, how data is stored has also evolved. In the past, data was siloed and fragmented, and it was difficult to find a consistent, consolidated view for making faster, strategic decisions. 

Today, with the rise of technology and cloud-based Big Data platforms, that has changed. Data warehouses on the cloud have emerged as the preferred way to store, manage and transform data. Data warehouses offer businesses a single, centralised view into data with real-time scalability. 

ETL (Extract, Load, Transform) is a process followed by companies to pull data from one source to another, and use it to run various data-driven applications for driving actionable insights.

The process goes as follows: 

  1. Extract: Firstly, the raw data is extracted in its raw form, including both homogeneous and heterogeneous sources.  
  2. Transform: Next, the data is transformed to a recognisable format suitable for the destination. 
  3. Load: Lastly, the transformed data is loaded into the source destination, ready to be used.

The cloud possesses endless possibilities, and this is where modern data warehousing options like Snowflake come into the picture. Snowflake is a data warehouse in the cloud built for fast moving businesses who want to transform and update data at the speed of change. Snowflake runs on popular cloud service solutions like AWS, Azure and Google Cloud. 

WIth its unique, custom architecture built for the cloud, Snowflake delivers performance, scale, speed and concurrency in one solution. Thanks to its simplified data processing, data users can easily store, analyse and transform data across separate data sources. Snowflake uses a hybrid, shared disk database architecture which consists of three distinct layers – database storage, query processing and cloud services. 

Snowflake ETL works well with a number of data integration tools such as – Informatica, Fivetran, Matrilion, etc. It also allows database users to work with a range of data formats and structures, including XML, JSON, CSVs and Parquet, and blend them parallely using SQL. 

Here’s how the 3-step process for Snowflake ETL works: 

Step 1: Extracting data from data source and generating data files in a distinct format such as CSV, JSON, Parquet, XML, etc. or in a combination of multiple formats. 

Step 2: Loading data into an internal or external storage

Step 3: Copying of data into the destination of a Snowflake database table. 

Snowflake also allows bulk loading of data from data sources. Now, let us look at the different benefits of using Snowflake’s cloud data warehouse platform: 

  1. Ease of use: With a simple and intuitive interface, Snowflake is easy to use and allows faster processing of data with its multi-cluster architecture. Snowflake makes it easier for anyone to replicate data from multiple sources. 
  2. Speed and Performance: With a cloud based database architecture, Snowflake allows bulk loading and processing of data, allowing higher volumes of data queries to be run virtually. Snowflake’s elastic cloud nature gives it the ability to scale up and take advantage of additional computing resources on demand.
  3. Accessibility and Concurrency: When a large number of database administrators and operators need access to data, it can lead to delays due to concurrent handling of data. With Snowflake, these concerns are addressed thanks to its multi-clustered architecture. Thus, each data warehouse can be scaled independently as per the requirements. 
  4. Seamless Data Sharing: With its multi-node architecture, Snowflake allows both users and applications to share data seamlessly among each other and within any other consumers of data, or readers. 
  5. Multi-format support: Be it XML, JSON or CSV, Snowflake supports multiple data formats, whether structured, unstructured or semi-structured. This makes Snowflake a single source of handling all types of data files which can exist in a database system.
  6. Instant Scalability: With its cloud architecture, Snowflake enables businesses to instantly scale their required resource bandwidth during high-demand periods.

According to industry experts, Snowflake’s cloud database platform is going to be the dominant choice for database solutions. The Snowflake tool is easy to use, which makes it friendly for companies and professionals of different scale and skill levels. 

If your business wants to migrate data from Oracle, SAP or SQL to Snowflake, then it’s time to choose a third-party platform like Bryteflow. With Bryteflow, your business can easily extract, load and transform any data without you requiring coding or software installation. 

Bryteflow replicates data in real-time with a fully automated process packed inside a user-friendly, intuitive interface. Further, you can stay on top of the data replication process by monitoring the status of data ingestion and transformation instances.