The StreamSets DataOps Summit brought together data engineers, enterprise architects, and data and analytics leaders from all over to discuss all things DataOps. (If you are unfamiliar with DataOps, this blog is a great place to start!)
Read on for our key takeaways from the event.
We Live in Data
Keynote speaker and self-proclaimed data artist, Jer Thorp, explained that we live in data: data is everywhere and impacts us every day of our lives in so many ways. From our clicks and likes to our consumption of news and reviews of everything we do, see, believe and feel, our world is statisi-fied or data-fied and categorized into understandable chunks of information, and that is how we make sense of it all.
DataOps Can Work for Everyone
The DataOps methodology is different from legacy approaches to managing and using data. DataOps promises better solutions through collaboration, greater trust in data and platforms, and better data quality. By integrating DataOps into your data ecosystem, you can modernize your data architecture and reap the benefits.
Learn more in Axis Group’s Guide to Modern Data Architecture.
Know Your Customer to Future-proof Your Infrastructure
There is a lot to consider when investing in new data capabilities including keeping an eye on the future to enable the digital transformation of your business and to take customers to new heights. As technologies and other requirements change, legacy architectures will not be able to keep up with your business needs. To stay relevant, you need to know your customer in order to create personalized and data-rich experiences.
Pick the Right Tool for the Right Job
Be sure to look at all the capabilities built into the data tools you use. Each tool likely has some level of capability for what you need, but factors such as licensing, training, infrastructure and other costs and potential impacts must also play a role in your evaluation. By looking at the capabilities and costs of the tools as well as the competencies on your team, you can determine which tools best fit your needs.
You Can Use Machine Learning to Make Music
DataOps is serious, but there was room for entertainment during the Summit. In a fun, hands-on session, Axis Group data engineers used StreamSet’s powerful MLOps capabilities to generate a MIDI file. The video can be found here.