Systems | Development | Analytics | API | Testing

Achieve Pin-Point Historical Analysis of Your Salesforce Data

Want to look at how data has changed over time? Simply enable history mode, a Fivetran feature that data analysts can turn on for specific tables to analyze historical data. The feature achieves Type 2 Slowly Changing Dimensions (Type 2 SCD), meaning a new timestamped row is added for every change made to a column. We launched history mode for Salesforce in May and have been delighted with the response.

Moving Big Data and Streaming Data Workloads to AWS

Cloud migration may be the biggest challenge, and the biggest opportunity, facing IT departments today - especially if you use big data and streaming data technologies, such as Cloudera, Hadoop, Spark, and Kafka. In this 55-minute webinar, Unravel Data product marketer Floyd Smith and Solutions Engineering Director Chris Santiago describe how to move workloads to AWS EMR, Databricks, and other destinations on AWS, fast and at the lowest possible cost.

Infrastructure and Software Development: What Got Us Here Won't Get Us There

In this fireside chat, industry leaders with experience driving revolutions in software development and infrastructure will discuss transitions to microservices, Kubernetes, cloud native and open source across industries. The panel will also discuss how requirements have changed, and what paths these technologies and architectures could take in the future.

Python Memory Management: The Essential Guide

Python is not known to be a "fast" programming language. However, according to the 2020 Stack Overflow Developer Survey results, Python is the 2nd most popular programming language behind JavaScript (as you may have guessed). This is largely due to its super friendly syntax and its applicability for just about any purpose.

Fivetran vs. MuleSoft vs. Xplenty : An ETL Comparison

The key differences between Fivetran, MuleSoft, and Xplenty: Hiring a data scientist or engineer can cost up to $140,000 per year —something many businesses can't afford. Still, organizations need to pull data from different locations into a data lake or warehouse for business insights. An Extract, Transform, and Load (ETL) platform makes this process easier, but few organizations have the technical or coding know-how to make it happen.

How leading organizations govern their data to find success

With the increased focus on delivering value customers, it is imperative to build a next generation customer hub that delivers high quality and governed data. In this video we will share best practices for implementing a comprehensive data governance approach. Learn how to leverage the capabilities of the Talend Data Fabric to deploy a forward-looking data management architecture that detects and retrieves metadata from across databases and applications, builds data lineage, and adds traceability.