knackforge
February 18, 2022
Big data is essential for any forward-thinking organization that requires more valuable business insights to better serve its customers and outperform its competitors. Unfortunately, many businesses aren’t capitalizing on the wealth of data that they have at their fingertips.
While working with this complex business data, you’re intended to unify and load this data into your desired destination at some point. While some data transfers are simple, others might be difficult owing to vast amounts of data and incompatibility between the source and destination.
Enterprises rely on data analytics to make the process easier. This is why both businesses and enterprises have chosen to install a data warehouse, a holistic data storage system that directly collects data from distinctive sources in the organization. However, this creates the issue of importing data from databases into a data warehouse in real-time.
Amazon introduced the cutting-edge ETL process, specifically designed to transfer data among enterprises from the source database directly into the data warehouse. Generally, ETL has incredible complexities and challenges that could be quite hard or sometimes impossible to deploy successfully for all business data. And this is the only reason why Amazon has tried to introduce a paradigm shift in terms of ETL tasks and processes with AWS Glue.
AWS Glue is a fully managed ETL service. ETL, which stands for extract, transform, and load, is the process data engineers use that involves extracting data from various sources, transforming it into a useable and trustworthy resource, and loading it into systems that end users can access and use downstream to address business issues. Amazon explains in detail that the entire system is designed to provide an easy and cheap way to not only categorize your data, but also clean, enrich, and transfer it efficiently between multiple data streams and data stores.
AWS Glue provides all the capabilities required for data integration so that you can start analyzing your data and putting it to use in minutes rather than months. To make data integration simple, AWS Glue offers both visual and code-based interfaces.
The major features of Glue include:
Serverless Computing: It is a serverless offering, which means you don’t have to manually designate a server to run it. Whenever you want to use its functionality, Amazon starts up a server for you and then shuts it down when it’s no longer in use. This automated provisioning relieves you of the burden of managing and scaling your infrastructure.
Apache Spark: Glue is based on the Apache Spark analytics engine for information processing. However, the service also permits users to create scripts in Python and Scala.
Easy Development: Users who want to manually write their ETL code have access to “developer endpoints”: environments in which you can develop and test your scripts.
Data Catalog: The Catalog is a metadata repository that holds information about all of your data stores and sources, allowing you to see your critical information regardless of location.
Job Scheduling: Glue simplifies scheduling by allowing you to start jobs based on an event or a schedule, or completely on-demand.
Requires Technical Knowledge - Some features of AWS Glue are not very friendly to non-technical beginners. For example, since all the tasks run in Apache Spark, you need to be well-versed in Spark to tweak the generated ETL jobs. Furthermore, only developers who are familiar with Python or Scala may work on the ETL code.
Requires Specific Skill Set - When it comes to customizing ETL codes, AWS Glue only supports two programming languages, Python and Scala.
Limited Integrations - AWS Glue is built in such a way that it works with other AWS services only. That means you won’t be able to integrate it with platforms outside the Amazon ecosystem.
AWS Glue is a fantastic solution for IT professionals and developers that allows them to reduce the overall complexity and manual labor involved in the ETL process. It is a powerful serverless, cost-effective service that offers simple tools to catalog, clean, enrich, validate and move your data for storage in data warehouses and data lakes.
It is also a well-established tool that is user-friendly, exponentially managed, and features strong support making it an outstanding ETL platform.
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