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SF Big Analytics 2019-06-12: Managing uber's data workflows at scale
The document outlines the roles and technologies related to data scientists and engineers at Uber, focusing on tools like Apache Kafka, Hadoop, and various BI apps. It includes legal disclaimers about trademarks and restrictions on the document's dissemination, emphasizing its proprietary and confidential nature. The content is intended solely for authorized recipients within the organization.
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- 89. Proprietary and confidential© 2019 Uber Technologies, Inc. All rights reserved. No part of this document may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage or retrieval systems, without permission in writing from Uber. This document is intended only for the use of the individual or entity to whom it is addressed and contains information that is privileged, confidential or otherwise exempt from disclosure under applicable law. All recipients of this document are notified that the information contained herein includes proprietary and confidential information of Uber, and recipient may not make use of, disseminate, or in any way disclose this document or any of the enclosed information to any person other than employees of addressee to the extent necessary for consultations with authorized personnel of Uber.