Snowflake ETL – Its Importance to Modern-day Businesses
Do you want to set up and maintain a dependable ETL (Extract, Transform, Load)process for your business but are not sure about the best tool to use? Are you a Snowflake customer and need to extract and load data from multiple sources? If these questions apply to you, this post will guide you through the many facets of Snowflake ETL and the key benefits that you can derive from it.
First a look at Snowflake and ETL and what both combined to bring to the table as Snowflake ETL.
Snowflake is a cloud-based platform offered as a Software-as-a-Service and is a fully-managed Data Warehouse. It has an edge over other platforms as it supports all types of data in their native format – unstructured, semi-structured, and structured like JSON, Parquet, and more. It adheres to all standard ANSI SQL protocols.
Snowflake is highly scalable as a data warehouse. Users have access to unlimited storage capabilities, paying only for the quantum of resources used. Further, it provides high computing powers with multipleusers able to simultaneously carry out intricate multiple queries without any drop or lag in performance.
The ETL Tool
The ETL in Snowflake ETL stands for Extract Transform and Load. The process involves extracting data from one or many sources, transforming it into compatible formats and structures, and finally loading the data into a data warehouse or a target database. The sources from where the data is extracted may include third-party applications, databases, and flat files. The core purpose of Snowflake ETL,therefore, is to apply the ETL activity to load data into a data warehouse of Snowflake. Data is extracted from multiple sources, formatted to match the data structures supported by the Snowflake architecture, and loaded onto the Snowflake platform.
Features of the top Snowflake ETL tools
If you are looking for Snowflake ETL tools, you will be spoilt for choice. You will get several tools that are either simple plug-and-play affairs or highly customized ones that ensure easy data movement from a range of data sources to Snowflake. The decision to be made here is which features of Snowflake ETLwill be required for your business and ideal for your operations.
Given here are some of the factors that need to be considered before investing in the Snowflake ETL tool that is perfect for you.
- Cost-effectiveness: This is always a priority for any organization and the choice is between opting for a paid or open-source tool. The point is should you prefer a tool that has been developed in-house or one that has been created by a reputed ETL service provider with the required expertise in this field.
- User-friendly: Snowflake ETL tools are available in a variety of forms. These range from writing SQL or Python scripts to simple drag and drop GUIs. All types ensure optimized transformations of the ETL process.
- Moving data from multiple data sources: Preferably, there should be one Snowflake ETL tool that takes care of every need, from data engineering to ETL. Hence, there should not be any problem with the tool if there is a large number of data sources.
- Possibility of modifying data sources: The majority of ETL providers offer support for a specific number of data sources. However, the top-of-the-line Snowflake ETL tools will leave space for custom addition and modification of the number of sources.
- Data transformation: Many tools focus primarily onthe extraction and the loading of data and offer very limited or almost nil transformation options. Hence, you should understand the extent of the transformation activities offered by Snowflake ETL.
- Pricing: This aspect is not standardized and is dependent on a large number of factors and use-cases. Hence, it is necessary that you carefully evaluate your requirements first and then the different ETL service providers so that you get the maximum returns from your investment. Buying expensive tools when you might not use even half the features will be a waste of money.
- Detailed product documentation: It is preferable that detailed product documentation is available for the tool so that, if necessary, your in-house engineers can troubleshoot any problem quickly.
- Customer support: What is critical when you invest in Snowflake ETL is timely multi-channel support whenever you need it.
Ensure that these attributes are considered when you choose Snowflake ETL for your organization.
In recent times, there is a new variant of the traditional Snowflake ETL that is increasingly becoming popular and that is ELT. As the acronym suggests, ELT stands for Extract, Load, Transform. The difference between the two is that in the new version, the data goes through transformations after it is loaded into a data warehouse or a target database. ELT is also gaining popularity as a means to move data to Snowflake.
Snowflake and ETL
In traditional scenarios, there might be several areas of failure while carrying out the ETL process. With Snowflake, the advantage is that it does away with the need for time-consuming, labor-intensive, and often chancy ETL processes. This is possible because data is made easily accessible for internal and external partners through the Snowflake Secure Data Sharing feature.
Snowflake also supports both types of transformations that is, before (Snowflake ETL)or after loading (ELT)and works with a wide range of data integration tools.
In data engineering, old tasks like manual ETL coding and data cleaning companies are no longer required with the introduction of new tools and self-service pipelines. Data engineers can now spend more time fruitfully working on vital data strategy and pipeline optimization projects with easy ETL or ELT options via Snowflake.
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