Data Virtualization: Introduction and Business Value (UK)
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This document provides an overview of a webinar on data virtualization and the Denodo platform. The webinar agenda includes an introduction to adaptive data architectures and data virtualization, benefits of data virtualization, a demo of the Denodo platform, and a question and answer session. Key takeaways are that traditional data integration technologies do not support today's complex, distributed data environments, while data virtualization provides a way to access and integrate data across multiple sources.
Data Virtualization: Introduction and Business Value (UK)
- 1. EMEA WEBINARS Data Virtualization Introduction and Business Value
- 2. Speakers Paul Moxon SVP Data Architecture & Chief Evangelist Denodo Director, EMEA Sales Engineering Denodo Mark Pritchard
- 3. Agenda1. The Need for Adaptive Data Architectures 2. What is Data Virtualization? 3. Benefits of Data Virtualization 4. Denodo Platform 8.0 Demo 5. Key Takeaways 6. Q&A 7. Next Steps
- 4. 4 Data Integration – A Journey Through Time… S Data Sources Data Ingestion Staging S Data Transformation External Data Consumers Web Logs, Click stream GEO location data Social Networks Sensor data Machine Generated New Data Sources
- 7. 7 Adaptive Data Architectures • Organizations need an adaptive data architecture • An architecture that can flex and adapt to new technologies, new data sources, new formats, new protocols, new data uses, etc. while minimizing the impact on the consumers • Future-proofs the architecture • We can’t predict what technologies will emerge in next 3-5 years (or 5-10 years), but we can build architectures that will accommodate them • Allows users to access new data, new technologies using existing, familiar tools • e.g. read data from a Parquet file using Excel (via the Data Virtualization Platform) • A Data Fabric – built on Data Virtualization – provides this adaptability and protects your existing technology investments and de-risks the adoption of new, emerging technologies
- 8. 8 Adaptive Data Architecture Reporting Analytics Data Science Data Market Place Data Monetization AI/ML iPaaS Kafka ETL CDC Sqoop Flume RawDataZoneStagingArea CuratedDataZoneCoreDWHmodel Data Warehouse Data Lake Data Virtualization Platform Analytical Views Data Science Views λ Views Real-Time Views DWH Views Hybrid Views Cloud Views UniversalCatalogofDataServices CentralizedAccessControl Enterprise Data Fabric
- 9. 9 Source: “Gartner Market Guide for Data Virtualization, November 16, 2018” Data virtualization can be used to create virtualized and integrated views of data in-memory rather than executing data movement and physically storing integrated views in a target data structure. It provides a layer of abstraction above the physical implementation of data, to simplify query logic.
- 10. 10 What is Data Virtualization? Consume in business applications Combine related data into views Connect to disparate data sources 2 3 1 DATA CONSUMERS DISPARATE DATA SOURCES Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word... Analytical Operational Less StructuredMore Structured CONNECT COMBINE PUBLISH Multiple Protocols, Formats Query, Search, Browse Request/Reply, Event Driven Secure Delivery SQL, MDX Web Services Big Data APIs Web Automation and Indexing CONNECT COMBINE CONSUME Share, Deliver, Publish, Govern, Collaborate Discover, Transform, Prepare, Improve Quality, Integrate Normalized views of disparate data “Data virtualization integrates disparate data sources in real time or near-real time to meet demands for analytics and transactional data.” – Create a Road Map For A Real-time, Agile, Self- Service Data Platform, Forrester Research, Dec 16, 2015
- 11. 11 How Does It Work? Development Lifecycle Mgmt Monitoring & Audit Governance Security Development Tools and SDK Scheduled Tasks Data Caching Query Optimizer JDBC/ODBC/ADO.Net SOAP / REST WS U Customer 360 View Virtual Data Mart View J Application Layer Business Layer Unified View Unified ViewUnified ViewUnified View A J J Derived View Derived View J JS Transformation & Cleansing Data Source Layer Base View Base View Base View Base View Base View Base View Base View Abstraction
- 12. 12 Data Virtualization Connects the Users to the Data That They Need 1. Data Virtualization allows you to connect to (almost) any data source 2. You can combine and transform that data into the format needed by the consumer 3. The data can be exposed to the consumers in a format and interface that is usable by them • Typically consumers use the tools that they already use – they don’t have to learn new tools and skills to access the data 4. All of this can be done without copying or moving the data • The data stays in the original sources (databases, applications, files, etc.) and is retrieved, in real-time, on demand Cliffs Notes version (TL;DR)
- 13. 13 Decoupling Business from IT IT: Flexible Source Architecture Business: Flexible Tool Choice IT can now move at slower speed without affecting the business Business can now make faster and more sophisticated decisions as all data accessible by any tool of choice
- 14. 14 Benefits of Using Data Virtualization • For Business Users • Simplicity: Users don’t need to navigate the complexity of the architecture. Where is data (on-prem, cloud, multi-cloud)? How to Access it? Which location has priority? • Agility: All data is securely delivered from a single (virtual) system • Accessibility: Data is accessible in a variety of formats (SQL, REST, OData, GraphQL) and in a web-based Data Catalog, regardless of original format and location • Common Semantic Layer: All users see the same definitions and data, providing data consistency • Governed Self-Service: Users can use their own tools (BYOT) to access and query the data that is governed, secure, and trusted data.
- 15. 15 Benefits of Using Data Virtualization • For IT • Abstraction: Decouples storage and processing engines from the delivery of data • Flexibility: Allows IT to change technologies and move data without service interruptions • Security: Centralized governance and security controls for all data assets • Governance: The data accessed by the users can be governed, secured, and managed so that users are accessing known, trusted, and approved data sets. • Accelerated Delivery: As data is not be replicated to a staging area or data mart for use, it is significantly quicker (up to 90% quicker) to deliver the data needed by the users.
- 16. 16 Data Virtualization Use Cases From Data Storage & Management, to Data Consumers, going through Data Governance & Security Real-time Decisions K.Y.C. (Customer 360) Self-Service Analytics Data Science (ML & AI) Apps (Mobile & web) Mergers & Acquisitions Data Marketplace Compliance (IFRS17, GRC) Data Security APIfication (& SQLification) Semantic Layer Agility & Simplicity Real-time Delivery Data Abstraction Zero Replication Data Governance Sophisticated Optimizations Logical Data Warehouse Enterprise Data Fabric Hybrid Data Fabric Data Integration Cloud Modernization Refactoring & Replatforming Data Consumption Data Storage & Management Data Governance, Manipulation & Access Sales HR Executive Marketing Apps/API Data Science AI/ML
- 17. 17 Denodo Platform 8.0 Demo
- 18. 18 Demo Scenario Distributed Data: ▪ Historical sales data offloaded to Hadoop cluster for cheaper storage ▪ Marketing campaigns managed in an external cloud app ▪ Customer details table, stored in the DW 1) On-board and expose distributed data through a single logical layer. 2) Publish a logical view calculating the impact of a new marketing campaign by country? Sources Combine, Transform & Integrate Consume Base View Source Abstraction Sales Campaign Customer Sales Evolution
- 19. Key Takeaways
- 20. 1. Information architectures are getting more complex, more diverse, and more distributed. 2. Traditional technologies and data replication don’t cut it anymore. 3. Data virtualization makes it quick and easy to expose data from multiple source to your users while still maintaining governance and security… 4. …and enables a wide range of use cases; from self- service analytics to data marketplaces to regulatory reporting and compliance. Key Takeaways
- 21. Q&A
- 22. 22 Next Steps Access Denodo Platform in the Cloud! Take a Test Drive today! www.denodo.com/TestDrive GET STARTED TODAY
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