Remove solutions data-lakehouse
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Data Lakehouse vs Data Warehouse in Microsoft Fabric

Advancing Analytics

A question that has come up a lot is whether to pick a Lakehouse or a Data Warehouse. In this blog post I will go through how to decide whether to choose a Lakehouse or a Data Warehouse artifact. Data can be stored as a folder, files, or databases and tables.

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A Well-architected Lakehouse with Hydr8

Advancing Analytics

By designing solutions around these principles, you can build high-quality solutions that are robust and cost effective. The step-up in technical maturity can be daunting for businesses to achieve - particularly when applied to cutting-edge technology like the Lakehouse.

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When is an Aggregate not an Aggregate?

Advancing Analytics

Could it be the slightly clumsy but somehow now de facto naming convention used for the Lakehouse layers? I recently asked that question on my Twitter feed , and aside from the odd joke about “small stones used for building” here are some of the responses I got: · It means you took the data from a lower grain to a higher grain.

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What is Microsoft Fabric? An Introduction

Advancing Analytics

That means Fabric is your one-stop-shop for your full data platform, from ingesting source data through to data visualisation across each persona, from Data Engineer to Power BI user and everyone in between. With Fabric, Microsoft are ambitiously embracing the Data Lakehouse architecture in a Mesh-like vision.

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Microsoft Fabric: An introduction to OneLake

Advancing Analytics

As data engineers, we face many challenges daily. Data is often distributed across many different sources, and frequently in a wide range of file types with varying levels of data quality. Data from these can be seen inside of respective workspaces within the same OneLake. What are the access rights?

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Microsoft Fabric: An End to End Implementation

Advancing Analytics

This blog will walk you through the entire data lifecycle of ingesting data from SharePoint and Azure Blob Storage, through the lakehouse pattern, and finally to the reporting stage - all using Microsoft Fabric. The Dataset The data comprises two tables in an Excel file. We will be selecting a lakehouse.

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Fabric and Tabular Editor

Advancing Analytics

In my time working with Advancing Analytics, I’ve continued to use it with Databricks lakehouses and have even developed our own solution accelerator with Tabular Editor to get people up and running with Power BI semantic models on the lakehouse fast. From workflow perspective, you have a few different options available.

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