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Expert Talk: Unlocking the Power of Real-Time Analytics
Adi Polak and Tim Berglund explore the concept of analytics and what it truly means in the software development world. They delve into the benefits of real-time analytics for product development, highlighting the fine line between compute and storage and the technical requirements for achieving effective real-time analytics. They also discuss the applications of real-time analytics through the lens of Apache Pinot and StarTree Cloud, exploring use cases such as the popular "Who's Watched My Profile on LinkedIn" feature powered by Apache Pinot.
IBM - Myths of Cloud
IBM will share a Point of View on myths of Cloud and how Enterprises deal with the even more complex world of Hybrid Clouds and traditional IT addressing Data, Analytics, Security, Management & Automation and not least Hybrid & Multi Clouds. IBM will update on its open approach to cloud, featuring unprecedented security and portability across multiple clouds and why it recently have announced intend to conduct the largest software acquisition* ever. IBM will also share an overview about its Cloud Adoption & Transformation practice and IBM Cloud Garage Methods which help clients monetizing benefits from Cloud platforms and AI. *As the RedHat aquisition is subject to regulatory approvals there will be limits to comments and what can be shared.
Introduction to Real-Time Analytics with Apache Pinot
When things get a little bit cheaper, we buy a little bit more of them. When things get cheaper by several orders of magnitude, you don't just see changes in the margins, but fundamental transformations in entire ecosystems. Apache Pinot is a driver of this kind of transformation in the world of real-time analytics. Pinot is a real-time, distributed, user-facing analytics database. The rich set of indexing strategies makes it a perfect fit for running highly concurrent queries on multi-dimensional data, often with millisecond latency. It has out-of-the box integration with Apache Kafka, S3, Presto, HDFS, and more. And it's so much faster on typical analytics workloads that it is not just a marginally better data warehouse, but the cornerstone of the next revolution in analytics: systems that expose data not just to internal decision makers, but to customers using the system itself. Pinot helps expand the definition of a "decision-maker" not just down the org chart, but out of the organization to everyone who uses the system. In this talk, you'll learn how Pinot is put together and why it performs the way it does. You'll leave knowing its architecture, how to query it, and why it's a critical infrastructure component in the modern data stack. This is a technology you're likely to need soon, so come to this talk for a jumpstart.
Bridging the Gap: How Data and Software Engineering Teams Can Work Together to Ensure Smooth Data Integrations
Imagine this scenario: The engineering team at your company is about to launch a new product or feature. The pressure is on the data team to deliver metrics and stats from the get-go, as everyone is keen to see how the new feature is performing. Behind the scenes, the data team is scrambling to understand how to connect to the new systems, transform the data, interpret it, and turn it into actionable insights. In this talk, I will walk the audience through the different steps necessary to ensure both data teams and software engineers are ready to integrate with a new production system and deliver correct and reliable analytics from day 1. I will cover topics such as infrastructure and data access considerations, data models, data flow and state changes, and data quality checks. I will also touch upon “data contracts”, a concept that’s been talked about a lot recently in the data space, and how these can be established to preserve consistent high-quality data integrations. Both data practitioners and software engineers will benefit from this talk and learn how to “bridge the gap” between the two worlds.