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Fixing guide typo (#4516)
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## What are you changing in this pull request and why?

Fixing a small typo in the Dremio guide

## Checklist

- [x] Review the [Content style
guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md)
so my content adheres to these guidelines.
- [x] For [docs
versioning](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/single-sourcing-content.md#about-versioning),
review how to [version a whole
page](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/single-sourcing-content.md#adding-a-new-version)
and [version a block of
content](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/single-sourcing-content.md#versioning-blocks-of-content).
- [x] Add a checklist item for anything that needs to happen before this
PR is merged, such as "needs technical review" or "change base branch."
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matthewshaver authored Nov 20, 2023
2 parents fd66117 + 5e0650d commit b6f1910
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2 changes: 1 addition & 1 deletion website/docs/guides/dremio-lakehouse.md
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Expand Up @@ -14,7 +14,7 @@ recently_updated: true
---
## Introduction

This guide will demonstrate how to build a data lakehouse with dbt Core 1.5 or new and Dremio Cloud. You can simplify and optimize your data infrastructure with dbt's robust transformation framework and Dremio’s open and easy data lakehouse. The integrated solution empowers companies to establish a strong data and analytics foundation, fostering self-service analytics and enhancing business insights while simplifying operations by eliminating the necessity to write complex Extract, Transform, and Load (ETL) pipelines.
This guide will demonstrate how to build a data lakehouse with dbt Core 1.5 or newer and Dremio Cloud. You can simplify and optimize your data infrastructure with dbt's robust transformation framework and Dremio’s open and easy data lakehouse. The integrated solution empowers companies to establish a strong data and analytics foundation, fostering self-service analytics and enhancing business insights while simplifying operations by eliminating the necessity to write complex Extract, Transform, and Load (ETL) pipelines.

### Prerequisites

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