If you like writing SQL and need a cheap data platform in Azure, this session is for you. This session will describe the architecture for a metadata driven, minimalistic Azure data platform using Synapse Analytics (serverless SQL) and data lake. You will get to know when this works well, and when it does not.
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Introductory session to Azure Data Explorer that shows some examples how to set up ADX and how to use it.
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Join this session to learn what Azure Data Explorer (aka Kusto) is, see it in action and get a quick start in this great platform for observational analytics.
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In this quest, we will investigate what kind of tool Tabular Editor is and how it can help you become a more efficient Power BI Wizard
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In this session, seasoned data engineer and youtube grumbler Simon Whiteley takes us on a journey through the current industry trends and buzzwords, carving through the hype to get at the underlying ideals.
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Data Governance is an enabler. Explore what the new world of Data Governance is and how we help businesses understand the benefits, why it is important, and how to get started in simple agile steps and where Microsoft Purview fits.
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Improve analytic queries by unlocking the secrets of columnstore compression!
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Are you able to fully understand the state of your data in your systems? Are you able to evaluate the quality of your data in all processes? In this session you will learn how easy it is to integrate HEDDA.IO into your existing processes, how it can provide you with a continuous view of the quality of your data and how it can inform you directly in the event of errors, warnings or major changes to individual parameters. HEDDA.IO brings data observability to your process and platforms.
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Modern software engineering and management for ETL, so data analysts and engineers can spend less time on tooling and focus on getting value from data.
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How you can collaboratively design a dimensional model with your business users
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Gain insight into how data can be loaded, processed, and uploaded to other environments in a self-service process from a wide variety of environments in a fully controlled and audited manner. Whether SQL Server, Data Lake, Delta Lake, SAP HANA or many other data sources and targets, WOODY.IO helps you implement clear governance processes into your self-service integration processes.
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Learn some of the root causes of high cloud bills and what you can do to solve them.
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HEDDA.IO is a central data quality management solution that connects departments, data stewards and data engineers. It helps to easily integrate standardization, cleansing, matching and enrichment tasks into existing processes.
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Be part of a live audience recording of an episode of Knee-Deep in Tech!
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What should you do when DirectQuery is the ONLY available option? How to reduce the data model size, while at the same time satisfying business requirements? I'll share tips, tricks and workarounds learned and implemented in real-life scenarios on enterprise data models.
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In this demo-rich session you will learn how you can implement a framework for data quality validation and monitoring, spanning your end-to-end data platform including Power BI!
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In this short session, we will go through the what, how and why of Power BI Datamarts. What is this feature you can find in Power BI Service? How can you use it to model your data, improve control and enable self-service? Why should you use Power BI Datamarts?
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Tired of writing the same old Insert/Update/Delete statements over and over? Is your pipelines folder overflowing? Need to get your new data warehouse up and running as fast as possible? Metadata (data about data) comes to the rescue and in this session we’ll show you how.
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Providing a business with an organized and propagated data catalogue is essential with ever growing demands and questions about your data platform. How are your data assets organised and how can you track lineage? In this session we will demonstrate how data landscaping can be achieved with Azure Purview and how business terminology and ownership can be assigned throughout.
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Are you planning a migrating of your data platform to Azure Synapse Analytics? Is it currently based on Azure Databricks, Azure Data Factory, and Azure Data Lake Storage? Make sure to grab these 10 tips! We'll talk about Spark compatibilities, orchestration pitfalls and solution deployment differences.
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