In this demo-filled session we get an overview of Azure Data Explorer, which is a fast, fully managed data analytics service for real-time analysis on large volumes of data streaming from applications, websites, IoT devices, and more. We look at how to ingest data, as well as query in real-time against billions of rows with sub-second latency.
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Using open source apache nifi to integrate and ingest data at scale
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Data Engineer is an exciting and rewarding role. This session will describe a data engineer's responsibilities and give an overview of the skills needed to be an Azure Data Engineer.
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Overview to some of the more popular Azure Data Engineering services used to analyze data
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Oh my goodness - the BI Power Hour is back!!
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This session will introduce you to "What and why you should care about", and discuss "how" to apply the Security and Privacy lens for Big Data on AWS.
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I'll explain the current popular data architectures: Data Lakehouse, Data Mesh, and Data Fabric
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In this session, we will cut through the marketing buzzwords to share experiences, tips, and tricks on how to be successful with Data Science and Analytics in the real world. Tune in to hear the team share real-world experience and get takeaways from industry insiders on real projects with impact. We will also discuss the ethics and fairness of Data Science and Analytics projects and how we can be more inclusive from a technology, people, and process standpoint.
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Session covering table distributions, partitioning , RSC and materialised views.
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Deployment == Return on investment. This session looks to show you how to do that for Machine Learning.
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Only the curious will learn and only the resolute overcome the obstacles to learning.
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Building a Data Quality implementation in Purview using the Glossary and Databricks
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Hybrid Transactional Analytical Processing solve the age old problem of integrating operational processes with analytical capabilities within a single system. Find out what they're and how they deliver value
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A session following the evolution of lakehouse architectures alongside the new techniques for code automation & metadata management they unlock
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Join me to learn how to migrate a traditional DW transformation process to Spark/Scala based platform and reuse existed experience
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Curious what Azure Synapse Analytics brings to the table? Bring your scuba gear, as we take a dive and explore everything it has to offer!
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There are several different data platform solutions for use within your application. Selecting the right option can make the difference between a well-performing application and a poorly performing one; not to mention the cost aspect of choosing the wrong solution.
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The "Meta-verse" - Using metadata to build your pipelines in less than 20 min
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Synapse Analytics Serverless SQL Pools and Pipelines are the dream team when it comes to managing big data in Azure Data Lake, this session will take you through the process!
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How has advancements in highly scalable cloud technology influenced the design principals we apply when building data platform solutions?
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