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Managed data integration is the best way for enterprises to get maximum value from their data — and their data engineering teams.

AWS Glue is a serverless Extract, Transform, Load (ETL) solution that helps organizations move data into enterprise-class data warehouses. It offers tight integration with other AWS services, which is attractive for organizations already heavily invested in this cloud ecosystem. But However, AWS Glue comes with a high learning curve and limited functionality compared to other ETL options. If you need a replacement for AWS Glue, here are the top 5 AWS alternatives in this guide.

Analysts and data scientists use SQL queries to pull data from the data storage underbelly of an enterprise. They mold the data, reshape it, and analyze it, so it can offer revenue-generating business insights to the company. But analytics is only as good as the material it works with. That is, if the underlying data is missing, compromised, incomplete, or wrong, so will the data analysis and inferences derived from it.

Informatica Power Center blends four data engineering products into one system, making it one of the most feature-rich but complicated ETL/ELT platforms on the market. With data management, app integration, API gateway, and iPaaS features, smaller teams that struggle to tame this all-encompassing tool might seek out an Informatica alternative instead.

Consider for a moment, if you will, plastic patio furniture. Plastic Fantastic is a global manufacturer with several factories, warehouses, and plenty of stores. One can only imagine the sheer amount of data resulting from sales, production, suppliers, and finances. Everything that happens, from purchase and onward, to these chairs, tables, and cupboards in all corners of the world is measured.

Reverse ETL and customer data platforms (CDPs) are two big data trends that have been receiving a great deal of attention. While both CDPs and reverse ETL can help you make smarter data-driven decisions, there are also several crucial points of distinction. In this article, we’ll answer the question: what’s the difference between reverse ETL and a customer data platform?

Migrating analytics workloads to the public cloud has been one of the most significant big data trends in recent years—and it shows no sign of slowing down any time soon. According to a study by IT research company Forrester: Within three years, however, Forrester predicts that the fates will have reversed: Of course, before data can be processed in the public cloud, it has to get there in the first place via data migration.

APIs are powerful for ETL (extract, transform, load) and data integration workflows. API integrations make it possible for the seamless exchange of information between websites, databases, and applications. The Xplenty API allows you and your enterprise to monitor Xplenty clusters and jobs. Through the Xplenty data processing package and Xplenty web application, you can call the Xplenty API to.

Data warehouses fixed one aspect of the data silo problem but introduced another. They function as a large, single source of truth for your organization, but getting insights from this data in a typical Extract, Transform, Load (ETL) data pipeline requires the use of Business Intelligence (BI) and analytics platforms. By the time your data team creates these reports and sends them to other business units, it’s too late for daily decision-making.

While traditional ETL (Extract, Transform, Load) collects data within a centralized data warehouse, reverse ETL flips the target and destination of the standard ETL process. This allows information to be pushed out of data warehouses and into powerful third-party operational systems that can provide better analytics and reporting services. With the Xplenty platform and its ETL tools, all information is sent between warehouses and third-party operational systems in an efficient and secure manner.