Systems | Development | Analytics | API | Testing

SNCF: Getting the customer experience right

As a major railway operator, SNCF has a whole lot of data on its hands, including more than 50 million customer records. The first step in using that data more effectively was integrating and consolidating all of its diverse data sources and databases into a single Customer Platform. In this video, Yann Jourdain, CIO at SNCF Voyages, explains how he made it happen.

TestQuality Test Management Tool for GitHub: Integration Steps, Defect & Issue Reporting process

TestQuality extends Github to provide Modern, Powerful, Test Plan Management. This is accomplished via a Deep Live Native 2-Way Integration between GitHub and TestQuality. Test Management workflows are extended so you can Create, Update, Delete, and Link Defects and Requirements in your GitHub repository without ever leaving your testing workflows. And best of all TestQuality is completely FREE for use with GitHub public repo's.

[Webinar] How To Reduce Selenium Scripts Maintenance by up to 90%

Selenium script maintenance can be a nightmare. Even a minor UI change can flood QA teams with endless repetitive work, yet while leaving broken locators and web loading issues are still undetected. In this webinar, Katalon experts will show how you can use Artificial Intelligence and Machine Learning to reduce Selenium script maintenance by up to 90%.

[DEMO] Bring data experts to solve data quality issues

Supporting data health is a team sport. In this video, learn how to engage all the data experts in your organization to fight bad quality data. Extend collaboration about data and enable self-service across your organization: Talend’s Data Inventory application enables your organization to easily collaborate across multiple business and technology functions and strengthen data integrity by centrally organizing datasets, consistently applying standardization rules and proactively correcting data errors.

Future of Data Meetup (2022): Using Apache Iceberg for Multi-Function Analytics in the Cloud

Iceberg is a high-performance table format intended for large-scale analytics that ensures easy accessibility of data stored in multiple file formats common in the Hadoop ecosystem for different use cases common in the lakehouse architecture. During this meetup, we’ll assume you’ve never heard of Apache Iceberg and explain the basics: what problems the Apache Iceberg project is addressing, how iceberg works, what features iceberg tables offer and how you can put Iceberg to use in your own data projects that utilize Hive, Spark, or Impala.