Add professional services references.

Author: igorborgest

README.md

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 ![AWS Data Wrangler](docs/source/_static/logo2.png?raw=true "AWS Data Wrangler")
 
+> An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative
+
 [![Release](https://img.shields.io/badge/release-1.8.0-brightgreen.svg)](https://pypi.org/project/awswrangler/)
 [![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler)
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

docs/source/index.rst

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+An `AWS Professional Service <https://aws.amazon.com/professional-services>`_ open source initiative.
+
 Quick Start
 -----------
 

docs/source/what.rst

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 What is AWS Data Wrangler?
 ==========================
 
-An `open-source <https://github.com/awslabs/aws-data-wrangler>`_ Python package that extends the power of `Pandas <https://github.com/pandas-dev/pandas>`_ library to AWS connecting **DataFrames** and AWS data related services (**Amazon Redshift**, **AWS Glue**, **Amazon Athena**, **Amazon EMR**, **Amazon QuickSight**, etc).
+An `AWS Professional Service <https://aws.amazon.com/professional-services>`_ `open source <https://github.com/awslabs/aws-data-wrangler>`_ python initiative that extends the power of `Pandas <https://github.com/pandas-dev/pandas>`_ library to AWS connecting **DataFrames** and AWS data related services (**Amazon Redshift**, **AWS Glue**, **Amazon Athena**, **Amazon EMR**, **Amazon QuickSight**, etc).
 
 Built on top of other open-source projects like `Pandas <https://github.com/pandas-dev/pandas>`_, `Apache Arrow <https://github.com/apache/arrow>`_, `Boto3 <https://github.com/boto/boto3>`_, `s3fs <https://github.com/dask/s3fs>`_, `SQLAlchemy <https://github.com/sqlalchemy/sqlalchemy>`_, `Psycopg2 <https://github.com/psycopg/psycopg2>`_ and `PyMySQL <https://github.com/PyMySQL/PyMySQL>`_, it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**.