Streaming analytics is crucial to modern business – it opens up new product opportunities and creates massive operational efficiencies. In many cases, it’s the difference between creating an outstanding customer experience versus a poor one – or losing the customer altogether. However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data.
Every API product manager wants as many developers as possible adopting and using their APIs. They want them to get to Hello World quickly and have a great developer experience (DX) along the way. Of course, the bigger goal is to be able to tie API success into the larger objectives of the company. For many, despite the best intentions, their metrics are too simplistic, narrow, and based on outdated models of engagement.
While there has been some incremental improvements in the last few years, there has been nothing significant recently - and I think there are four clear reasons for that. Firstly, there has been a lot of consolidation in the industry recently. When that happens, behemoth vendors focus far more on selling than building new products that are going to disrupt the industry.
Avoiding a common pitfall in data science by enabling history mode.
Use schemas to make life easier for your analysts and engineers.