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With billions of Internet of Things (IoT) devices, achieving real-time interoperability has become a major challenge. Together, Confluent, Waterstream, and MQTT are accelerating Industry 4.0 with new Industrial IoT (IIoT) […].
Intro A very common use case in data engineering is to build a ETL system for a data warehouse, to have data loaded in from multiple separate databases to enable data analysts/scientists to be able to run queries on this data, since the source databases are used by your applications and we do not want these analytic queries to affect our application performance and the source data is disconnected as shown below.
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MongoDB is the most popular NoSQL database today, by some measures, even taking on traditional SQL databases like MySQL, which have been the de facto standard for many years. MongoDB’s document model and flexible schemas allow for rapid iteration in applications. MongoDB is designed to scale out to massive datasets and workloads, so developers know they will not be limited by their database.
Apache Kafka® is a distributed commit log, commonly used as a multi-tenant data hub to connect diverse source systems and sink systems. Source systems can be systems or records, operational […].
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Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Get step-by-step instructions to set up Teradata Vantage and author AWS Glue Streaming ETL jobs to stream data into Vantage from Amazon Kinesis and visualize the data.
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Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
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Challenges with our Tech Radar The Zalando Tech Radar is modelled after the Thoughtworks Technology Radar and includes a ring-based scoring for a certain technology/framework along with supplementary information about pros, cons, restrictions, usage, and lessons learned at Zalando available as a knowledge base for our teams. Since publishing, the approach and visualization engine has been used by others and also showcased at conferences as an example of how tech companies manage their technology
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