From 71adc1e3dadf8ee18dc4f8c763d3faae7e5decff Mon Sep 17 00:00:00 2001
From: Lucas Van Dijck <78962099+lucasvandijck@users.noreply.github.com>
Date: Mon, 23 Oct 2023 09:31:05 +0200
Subject: [PATCH] Typo

Fixed a typo in the word Analytics
---
 docs/strategy/business-outcomes/data-innovations.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/strategy/business-outcomes/data-innovations.md b/docs/strategy/business-outcomes/data-innovations.md
index 35b203ab70..27a02921fb 100644
--- a/docs/strategy/business-outcomes/data-innovations.md
+++ b/docs/strategy/business-outcomes/data-innovations.md
@@ -16,7 +16,7 @@ Many companies want to migrate their existing data warehouse to the cloud. They
 - No infrastructure to manage.
 - The ability to switch to a secure, scalable, and low-cost cloud solution.
 
-For example, Azure Synapse Analyticcs is a cloud-native, pay-as-you-go service which provides an analytical database management system for organizations. Azure technologies can help modernize your data warehouse after migration, and extend your analytical capabilities to drive new business value.
+For example, Azure Synapse Analytics is a cloud-native, pay-as-you-go service which provides an analytical database management system for organizations. Azure technologies can help modernize your data warehouse after migration, and extend your analytical capabilities to drive new business value.
 
 A data warehouse migration project involves many components. These include schema, data, extract-transform-load (ETL) pipelines, authorization privileges, users, BI tool semantic access layers, and analytic applications.