The key differences between Stitch, Jitterbit, and Xplenty: The average business pulls data from 400 different locations, which makes it tricky to generate valuable data insights. Data-driven organizations use an Extract, Transform, and Load (ETL) platform to pull all this information into a data lake or warehouse for deeper analysis. However, many businesses lack the technical skills (like coding) to facilitate this process. The three tools in this review make ETL workflows easier.

Along with the functionality to make HTTP requests, Xplenty provides various Curl functions and advanced features that can be beneficial in certain use cases. This article covers the Curl functions and features in addition to providing a step-by-step demonstration.

Cybercriminals are currently enjoying a golden age. The sudden shift to remote working, combined with the digitization of everyday life, means endless opportunities to compromise systems and access sensitive data. If you don't want your organization to be their next victim, you must have to know how to prevent data breaches.

During data analysis in SQL, one will often need to look at multiple tables and join them to get the desired results. Joining tables for analyzing data is a required skill for a data scientist or data engineer. Selecting the right join will optimize query performance.

The main differences between Alooma, MuleSoft, and Xplenty: Data-driven organizations pull data from multiple locations such as in-house databases, SaaS, and cloud-based apps, making it difficult to determine accurate business insights. Moving all this information into a single location makes data analytics easier. This is where Extract, Transform, and Load (ETL) comes in.

The key differences between Amazon Kinesis and Kafka are: Introducing data streamers! These services validate and route messages from one application to another, managing workload and message queues effectively. The result? Users process messages through a centralized processor and handle large data streams more efficiently. Amazon Kinesis and Apache Kafka are two data stream services.

The Health Insurance Portability and Accountability Act, or HIPAA, is a federal regulation in the United States that protects healthcare data containing personal health information, or PHI. It also covers Electronic PHI, or E-PHI, which are digital records of this information. The ability to effectively using healthcare data is essential for improving patient outcomes, quality of care, resource allocation, revenues, and other operations.

A Big Data stack has several layers that take your data from source to analytics tools. Extract, Transform, Load tools integrate data from sources into a data warehouse or lake. Business intelligence solutions use centralized data for their analytic needs. An ETL tool such as Xplenty offers a user-friendly experience for ingesting data from many sources, transforming it as needed, and sending it to the next layer. Here’s how you can implement this handy tool in your organization.

The major differences between Jitterbit, MuleSoft, and Xplenty: Extract, Transform, and Load (ETL) streamlines data integration by consolidating data from multiple sources, turning it into useful formats, and loading it into a centralized location. The world's most successful organizations use ETL to tame big data, produce visual data flows, and garner business-critical analytics. But with so many ETL tools on the market, which one should you choose?

Today we are delighted to introduce our new Workspaces feature that allows users to organize and group their packages together. It’s always been a bit challenging to organize packages within Xplenty especially if you have hundreds of packages, or if there are many users using the account. Finally, all those issues should be addressed by the new Xplenty Workspace feature.