Why Your Customer Data Platform Should Be the Data Warehouse
Off-the-shelf customer data platforms have serious shortcomings. Consider data warehouses instead.
Off-the-shelf customer data platforms have serious shortcomings. Consider data warehouses instead.
As part of the UnitedHealth Group (UHG), Optum optimizes healthcare technology, and one of our important missions is to provide the tech infrastructure for this Fortune 7 healthcare giant. UHG has over 300,000 employees, thousands of APIs, and countless integrations and external systems. It’s safe to say that a lot happens in our environments.
Ep. 8: Tyler Jewell, Managing Director at Dell Technologies Capital Joining us is Tyler Jewell, a Managing Director at Dell Technologies Capital. Before that he was the CEO of API Management platform company WS02. As an investor he’s placed almost $150M in DevOps companies and is a self-confessed geek in dev tools, devops, infrastructure and dev platforms.
Microservices, also known as microservices architecture, refers to a method of designing and developing software systems. Microservice architecture is becoming increasingly popular as developers create larger and more advanced apps. The goal is to help enterprises become more Agile, especially as they adopt a culture of continuous testing. Here are the basic features of microservices.
Over the last few days, I have been hard at work writing an up to date comparison of Kubernetes tooling (check out the first and second posts if you haven’t already, which cover tools that help you reproduce issues locally). Going through the sprawling Kubernetes ecosystem and curating the knowledge that would be the most interesting to fellow developers and engineering managers has been no small task. That’s why section 3 will cover the heart of cloud-native development: the IDE.
Over the last few blog posts, I have covered critical elements of developer tooling for Kubernetes and how things are looking in 2021. As we continue to dive into that discussion, we must not forget the process of building container images. Of course, most of us create our images by writing Dockerfiles and building them with the Docker engine. And yet, more and more teams are adopting newer alternatives.
We live in a world where FinTech automation is forcing traditional banks to move faster and deliver better customer experiences. This new world demands a completely different business model from traditional financial institutions.
With product analytics, you collect data about how your users are interacting with features and how frequently they use your app. With website analytics, you know your top pages, devices, and locations, and you can drill down into activity per visitor. But what about manual app testing analytics?
Xplenty provides features to efficiently extract, transform, and store data from various sources. Chartio provides Visual SQL features that let us explore and analyze data. Furthermore, it includes functionality to arrange charts and metrics in dashboards that can be shared. Both these tools can be used synergically. In this post, we will cover how you to configured Xplenty to use Chartio data. In a subsequent post, we will explain how to visualize the data provided by Xplenty in Chartio.