Once again, the Gartner Catalyst event in San Diego, California provided another perfect setting for the 2,500 attendees and roughly 150 sessions. Many technology initiatives and topics were discussed, so we wanted to highlight our favorite takeaways.
New this year, we provided a lounge area to give attendees a place to rest, recharge, and get caught up on email. We were excited to unveil our latest messaging at the event: SingleStore, the No-Limits Database™ for modern applications.
Here were some of our favorite data and analytic sessions:
Preparing for 2019: Future-Proof Your Data and Analytic Strategy With New Architectural Patterns That Matter by Carlton Sapp.
In this talk, Carlton described the importance of preparing for the known and unknown data architecture requirements ahead. In the same vein that we all should have our personal safety and well being prepared or “prepped”, the same should be done with your data and analytics strategy. Salient points included evolving data ingestion with high reactive or stream processing. Persisting data with more structure leveraging data lake zones, and adding AI/ML in data management through embedded intelligence in data warehouses.
Kafka – The Essential Broker by Thornton Jared Craig.
Thornton, or TJ for those “in the know”, did a great job explaining the essentials of Apache Kafka, a modern distributed messaging platform for real-time workloads. A key takeaway from the talk included using Kafka for enabling a reactive data ecosystem that can deliver in-stream functions on the data including transformation, data quality, and filtering.
How Kafka and Modern Databases Benefit Apps and Analytics by Neil Dahlke.
Our very own solutions architect Neil, spoke to a standing-room-only crowd about the advantages of pairing Kafka with SingleStore for the ultimate analytics platform. Neil explained the architecture of SingleStore and why it’s perfectly suited to ingest, persist, and analyze data from Kafka topics.
Note: A replay of the popular talk is available here.
Using AI/Machine Learning With Your Data Warehouse by Henry Cook.
This was an extremely rich and practical session on how to leverage advanced analytic techniques including AI/ML functions with your data warehouse. Henry covered a number of analytic functions including linear regression, association or basket analysis, text analysis, and more. An exciting new innovation is the use of ML to automate data transformation and classification including time series, gap filling, and image processing.
Five Ways Database Modernization Simplifies Your Data Life by Mike Boyarski.
In my talk, the goal was to describe some of the latest challenges faced by database professionals and how modern techniques can be used to solve them. The talk highlighted five specific database limitations with real-world customer examples for each. The limits included: speeding up the event to insight process, improving concurrency, delivering cost-effective performance, accelerating big data, and addressing deployment flexibility. The session slides can be viewed here.
While the topics ranged from cloud platform selection, new DevOps models, ML/AI, IoT architectures and more, one thing remained steady throughout, the pace of innovation continues to accelerate and the vendors available to help remain vast. This suggests shows such as Gartner Catalyst will continue to provide help and guidance on what tools to use for organizations trying to innovate their technology strategy.
