Systems | Development | Analytics | API | Testing

This video shows how Qlik can pre-build an entire end-to-end platform for cloud analytics, from extracting the data, transforming it in the warehouse and delivering analytics ready content – all in a single accelerator package.

In this session, Unravel CDO and VP Engineering Sandeep Uttamchandani describes the start of any large, data-driven project: the Discover phase. You must identify the insights you want to generate from the project, you must discover; that is, you must identify the current data assets you have, and the new data assets you will need, to generate the insights you want to produce. Sandeep expertly guides you through this process, and shows you how to invest the right amount of time and effort to get the job done.

In recent years, there’s been a shift towards JavaScript test automation frameworks. Today many Sauce Labs customers are using Cypress, TestCafe, Puppeteer and most recently Playwright.

Authentication can be difficult, but with the Kong Gateway JWT Plugin, you can save time and resources without risking your API gateway security. In this video, we'll walk through how to secure a service (in this case, an API server) with Kong Gateway and its JWT plugin. We’ll cover all the steps to set up, configure and test the service — giving you the foundational knowledge needed to implement these tools independently.

In this video, we will talk about how our customers are leveraging Apigee Analytics and Monitoring to gain meaningful insights into their API Programs.

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 Google Dataproc, BigQuery, and other destinations on GCP, fast and at the lowest possible cost.

In this video, we'll walk through an example on how you can use Cloudera Data Engineering to pull in multiple datasets from a Hive data warehouse and go through the process of enriching the data through the use of Apache Spark. We'll then run this Spark job from within Cloudera Data Engineering so that we can follow the progress and see details about the job's execution.