At a recent cloud technology conference, Amazon Web Services (AWS) launched a tool to help streamline data analytics in the cloud. This new tool, named “Glue,” is designed to help reduce the burden on engineers and employees so they can get down to the important elements of data analytics. Read on for an explanation of the AWS Glue and all the ways it can benefit your business.
Data analysis can be an extremely profitable arm of your business, if undertaken carefully. Much of what people consider to be data analysis for a business is actually just digital clerical work, which makes the process even more frustrating and time-consuming than it needs to be. At its core, AWS’s Glue is an app that automates this tedium, which is often referred to as ETL (extract-transform-load).
Third-party software already exists to help with this task, but the service from AWS is one of the first cloud-based alternatives to come to market. Glue is designed to work with businesses that have their own on-premises data centers and infrastructures in addition to working with AWS frameworks. In fact, if a business makes changes to on-premises data, Glue can be set up to trigger jobs and update the data in the cloud so users always have access to the most up-to-date information for use and analysis.
Essentially, AWS extracts various types of data from a wide array of sources and analyzes it, ultimately homogenizing the data to fit the business’s existing database. This eliminates a great deal of work because the extremely tedious task of importing data is often done by hand. Handing this burden over to AWS allows businesses to focus on the real analysis work; saving effort, time, and money in the process.
Every day, data becomes more and more integral to building a successful company. And with such a heavy burden placed on this facet of business, falling behind on the technology that makes it possible is an expensive mistake. If you’re hosting large amounts of data on-premises or in an AWS database, contact us today about how you can eliminate costly ETL processes.
Published with permission from TechAdvisory.org. Source.