From the course: Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) Cert Prep by Microsoft Press

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Ingesting data by using continuous integration from OneLake

Ingesting data by using continuous integration from OneLake - Microsoft Fabric Tutorial

From the course: Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) Cert Prep by Microsoft Press

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Ingesting data by using continuous integration from OneLake

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Ingesting data by using continuous integration from OneLake. Now with this, we're looking at loading data into Fabric OneLake automatically. And we can do this using different methods. The first we'll look at is Event House OneLake availability. Now this can be done on a KQL database and it allows a one-way synchronization of data data from that KQL database into Delta format within OneLake. Now the benefit of that is that other engines can then query that data in OneLake. You can shortcut from lake houses into this OneLake data, access it through Spark and other engines, even use semantic models with direct lake on this data. Now in the KQL database itself, we can set the one lake availability at the whole KQL database level, or if we only want individual tables, we can click on the table and select one lake availability and enable it. So if we don't want it at the whole database level, we can do it at the individual table level. Now in terms of event-driven processes, for example…

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