Fix typo in README.md

CHANGELOG.md

@@ -3,7 +3,11 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), 
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). 
-
+
+## [Unreleased]
+### Changed
+- Fix typos in README.md ([issues/50](https://github.com/aws-solutions/aws-data-lake-solution/issues/50))
+
 ## [2.1.1] - 2019-08-28 
 ### Added 
 - CHANGELOG templated file 

README.md

@@ -2,7 +2,7 @@
 
 Many Amazon Web Services (AWS) customers require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an increasingly popular way to store and analyze data because it allows businesses to store all of their data, structured and unstructured, in a centralized repository. The AWS Cloud provides many of the building blocks required to help businesses implement a secure, flexible, and cost-effective data lake.
 
-The data lake solution is an automated reference implementation that deploys a highly available, cost-effective data lake architecture on the AWS Cloud.  The solution is intended to address common customer pain points around conceptualizing data lake architectures, and automatically configures the core AWS services necessary to easily tag, search, share, and govern specific subsets of data across a business or with other external businesses. This solution allows users to catalog new datasets, and to create data profiles for existing datasets in Amazon Simple Storage Service (Amazon S3) and integrate with integrate with solutions like AWS Glue and Amazon Athena with minimal effort.
+The data lake solution is an automated reference implementation that deploys a highly available, cost-effective data lake architecture on the AWS Cloud.  The solution is intended to address common customer pain points around conceptualizing data lake architectures, and automatically configures the core AWS services necessary to easily tag, search, share, and govern specific subsets of data across a business or with other external businesses. This solution allows users to catalog new datasets, and to create data profiles for existing datasets in Amazon Simple Storage Service (Amazon S3) and integrate with solutions like AWS Glue and Amazon Athena with minimal effort.
 
 For the full solution overview visit [Data Lake on AWS](https://aws.amazon.com/answers/big-data/data-lake-solution).