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What if you could combine decades of historical analysis with live, real-time data in one seamless AI chat experience?
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Slow and inefficient Power BI reports are a widespread cause of low customer satisfaction, bloated costs, wasted compute capacity, and increased total cost of ownership.
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When working in the field of data and analytics, have you ever heard concerns about maintaining a single source of truth?
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For the past two years I’ve been working with my colleague Inder Rana to build out a GitHub repo that can be leveraged by Fabric users for training and testing purposes.
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Figure 2.0 – Snowflake and Fabric / Power BI integration options Back in September I published an article reviewing options for sharing lakehouse format data amongst Fabric, Snowflake, and Databricks.
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We are currently experiencing a generational surge in AI use cases and transformation.
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For many years, SQL Saturday conferences around the world have provided fantastic educational opportunities for professionals specializing in Microsoft tools such as Fabric, Power BI, and SQL Server.
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This post examines strategies to reduce data duplication and enhance performance by enabling shared access to data at rest across Snowflake, Databricks, and Microsoft Fabric.
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I have been collaborating with my colleague Inder Rana on a GitHub repository for an end-to-end Microsoft Fabric solution for some time, as it provides a simple means to learn about Fabric with real open source healthcare data.
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I’ve been sharing insights on data technologies through blogs, videos, and podcasts for over 15 years.