Data Virtualization enabled Data Fabric: Operationalize the Data Lake (APAC)
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The document details a webinar series focused on data virtualization, highlighting its role in overcoming data integration challenges, particularly within data lakes and big data fabric. Key topics include the structure of modern data ecosystems, customer case studies (notably Logitech's usage of data virtualization for flexible analytics), and the importance of data governance. The discussion emphasizes the need for curated repositories that enable semantic consistency and access controls for effective data management.
Data Virtualization enabled Data Fabric: Operationalize the Data Lake (APAC)
- 1. DATA VIRTUALIZATION APAC WEBINAR SERIES Sessions Covering Key Data Integration Challenges Solved with Data Virtualization
- 2. Data Virtualization enabled Data Fabric: Operationalize the data lake Chris Day Director, APAC Sales Engineering, Denodo Sushant Kumar Product Marketing Manager, Denodo
- 3. Agenda 1. The Reality of Data Lakes 2. Big Data Fabric 3. Customer Case Study – Logitech 4. Demo 5. Q&A 6. Next Steps
- 4. 4 A Modern Data Ecosystem 4
- 5. 5 The Promise of the Data Lake The promise of a data lake is a place that you can store data in its raw form, unencumbered by validation, mastering, or quality processes, so as to allow consumers to choose what data is of value to them with a quick time to market.
- 6. 6 …Data lakes lack semantic consistency and governed metadata. Meeting the needs of wider audiences require curated repositories with governance, semantic consistency and access controls.”
- 7. 7 Data Lake (System ofInsight) Information Management andGovernance Data Lakes and Big Data Fabric 1 Multiple repositories, organized based on source and usage; hosted on appropriate data platform for workload 1 Catalog of data, ownership, meaning and permitted usage 2 No direct access to repositories3 Curation of all data to define meaning and classifications 4 Business-led information governance and management 5 Active monitoring and management of data6 Data-centric security7 Access to raw data to developnew production analytics 8 Moderated, view-based self-service access to data and analytics for Line of Business 9 2 3 4 5 6 7 8 9
- 8. 8 Forrester’s Big Data Fabric
- 9. 9 Data Virtualization Big Data Fabric and Data Virtualization
- 10. 10 Data Virtualization Reference Architecture Security Governance and Metadata management DataWarehouse Unstructured Data RDBMS Excel FlatFiles XML Email Sensors (IIoT) SocialMedia Storage RDBMS Big Data Lakes noSQL IMDG Structured Data Data Ingestion Real Time/Streaming Wearables RFID Compute Batch CDC Data Access Metadata Enrichment Search and Index Data Virtualization Data Services Data Insight DataMining Dashboards Data Discovery andSelf-Service Reporting DATA VIRTUALIZATION
- 11. 11 Data Virtualization Reference Architecture Security Governance and Metadata management DataWarehouse Unstructured Data RDBMS Excel FlatFiles XML Email Sensors (IIoT) SocialMedia Storage RDBMS Big Data Lakes noSQL IMDG Structured Data Data Ingestion Real Time/Streaming Wearables RFID Compute Batch CDC Data Access Metadata Enrichment Search and Index Data Virtualization Data Services Data Insight DataMining Dashboards Data Discovery andSelf-Service Reporting DATA VIRTUALIZATION
- 12. 12 Customer Case Study – Logitech • Logitech also needed more agile (and cost effective) analytics platform for customer analytics • Moved analytics to AWS – utilized many different storage and compute capabilities on AWS • Redshift, Snowflake for EDW, RDS for relational data, S3 for data ingestion • Spark, EMR, NLP for analytics • Used Data Virtualization as data access layer • Users could access data irrespective of storage or processing capability • Data Virtualization Layer provided data security/access permissions • Abstracted security from different data sources • Data governance also provided by Data Virtualization Layer • Data lineage, metadata management, data catalog and discovery, etc.
- 13. 13 Customer Case Study – Logitech
- 14. 14 Customer Case Study – Logitech
- 15. 15 Customer Case Study – Logitech
- 16. 16 Summary • Big Data initiatives can add deep analytical insight to help organizations find new opportunities or provide more efficient services • When defining your Big Data initiative, think about how users will find and access the data • A Big Data Fabric is key to making this easy • And making the initiative successful • Data Virtualization is the right technology for an agile and flexible Big Data Fabric
- 17. Product Demonstration Director, APAC Sales Engineering, Denodo Chris Day
- 18. Q&A
- 19. 19 Next Steps Access Denodo Platform in the Cloud! Take a Test Drive today! https://bit.ly/2AouQLQ GET STARTED TODAY
- 20. 20 Next Steps
- 21. Next session How Data Virtualization adds value to your Data Science stack Sushant Kumar Product Marketing Manager, Denodo Chris Day Director, APAC Sales Engineeing, Denodo
- 22. Thanks! www.denodo.com [email protected] © Copyright Denodo Technologies. All rights reserved Unless otherwise specified, no part of this PDF file may be reproduced or utilized in any for or by any means, electronic or mechanical, including photocopying and microfilm, without prior the written authorization from Denodo Technologies.