Introduction to Modern Data Virtualization (US)
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The document outlines a webinar hosted by Denodo, focusing on modern data virtualization and its benefits in addressing challenges associated with data management such as complexity, cost, and security. It introduces the Denodo Standard as a solution for creating integrated and virtualized data views without physical data movement, enhancing decision-making through real-time information access. Key capabilities include data abstraction, self-service data services, and centralized governance, promoting streamlined access to trusted data for both business and IT users.
Introduction to Modern Data Virtualization (US)
- 1. DENODO WEBINARS Introduction to Modern Data Virtualization
- 2. Speakers Paul Fearon Senior Solutions consultant Denodo Sr. Sales Engineer Denodo Shehan Xavier
- 3. Agenda ❖ Challenges of Data Management ❖ What is Modern Data Virtualization? ❖ And how does it work. ❖ Benefits of Data Virtualization ❖ Introducing Denodo Standard ❖ Q&A
- 4. Challenges of Data Management
- 5. #DenodoDataFest Current Challenges of Data Management 1. Faster & more complex demands for decision making ▪ Provide useful information for decision making at all organization levels ▪ New users with advanced analytical skills and needs: e.g. data scientists ▪ Solution? Self Service Initiatives lead by business users, etc. → Either too complex (direct access) or too costly (specific data marts) , Governance and consistency problems 2. Regulations, enterprise-wide governance & data security ▪ Tens of new regulations worldwide: tax, finance, privacy, HR, environmental, etc. ▪ Ensure consistency in semantics of delivered data and data quality ▪ Enforce security policies ▪ Solution? Data Governance tools. Separate, static system for documentation→ get out of sync easily, don’t enforce policies & don’t deliver data to users 3. Complexity of DM infrastructure: IT cost reduction ▪ Huge data growth, operation costs → IT is looking for cheaper and more flexible solutions ▪ Solution? Cloud, Data Lakes → Increase integration complexity in the short term. E.g. Gartner says “83% of Data Lakes projects have failed”
- 6. 6 “Point-to-point integration is the simplest form of integration, but it can introduce technical debt with a complex spaghetti architecture that is hard to manage and change.” Gartner 2018, Where Does Point-to-Point Integration Belong in Your Integration Strategy? The end result of this approach for enterprises was described by Gartner as: “…unregulated, chaotic integration spaghetti.” Gartner 2017, Accelerating Digital Transformation in Insurance
- 7. 7 IT Architecture is Unmanageable & Brittle because: Business – IT Dilemma IT responds by loosely stitching together disparate data sources Any changes break the flow and affect business continuity Business Wants All of the Data, Now – So IT creates 100s to 1000s of brittle direct connections and replicates large volumes of data Inventory System (MS SQL Server) Product Catalog (Web Service -SOAP) BI / Reporting JDBC, ODBC, ADO .NET Web / Mobile WS – REST JSON, XML, HTML, RSS Log files (.txt/.log files) CRM (MySQL) Billing System (Web Service - Rest) ETL Portals JSR168 / 286, Ms Web Parts SOA, Middleware, Enterprise Apps WS – SOAP Java API Customer Voice (Internet, Unstruc)
- 8. What is Data Virtualization?
- 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 Structured More 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
- 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 View Unified View Unified View A J J Derived View Derived View J J S Transformation & Cleansing Data Source Layer Base View Base View Base View Base View Base View Base View Base View Abstraction
- 13. 13 Six Essential Capabilities of Data Virtualization 4. Self-service data services 5. Centralized metadata, security & governance 6. Location-agnostic architecture for multi-cloud, hybrid acceleration 1. Data abstraction 2. Zero replication, zero relocation 3. Real-time information
- 14. 14 1. Data abstraction Abstracts access to disparate data sources. Acts as a single virtual repository. Abstracts data complexities like location, format, protocols …hides data complexity for ease of data access by business Enterprise architects must revise their data architecture to meet the demand for fast data.” – Create a Road Map For A Real-time, Agile, Self-Service Data Platform, Forrester Research
- 15. 15 2. Zero replication, zero relocation …reduces development time and overall TCO The Denodo Platform enables us to build and deliver data services, to our internal and external consumers, within a day instead of the 1 – 2 weeks it would take with ETL.” – Manager, Enervus Leaves the data at its source; extracts only what is needed, on demand. Diminishes the need for effort-intensive ETL processes. Eliminates unnecessary data redundancy.
- 16. 16 3. Real-time information Provisions data in real-time to consumers Creates real-time logical views of data across many data sources. Supports transformations and quality functions without the latency, redundancy, and rigidity of legacy approaches …enables timely decision-making Denodo’s data fabric design relies on data virtualization to provide integrated data quickly to business users to effect faster outcomes..” – Gartner Magic Quadrant for Data Integration Tools, 18 August’ 2020
- 17. 17 4. Self-service data services Facilitates access to all data, both internal and external Enables creation of universal semantic models reflecting business taxonomy Connects data silos to provide best available information to drive business decisions …enables information discovery and self-service Impressively quick turn around time to "unlock“ data from additional siloes and from legacy systems - Few vendors (if any) can compete with Denodo's support of the Restful/Odata standard - both to provide data (northbound) and to access data from the sources (southbound).” – Business Analyst, Swiss Re
- 18. 18 5. Centralized metadata, security & governance Abstracts data source security models and enables single-point security and governance. Extends single-point control across cloud and on-premises architectures Provides multiple forms of metadata (technical, business, operational) to facilitate understanding of data. …simplifies data security, privacy, audit Our Denodo rollout was one of the easiest and most successful rollouts of critical enterprise software I have seen. It was successful in handling our initial, security, use case immediately, and has since shown a strong ability to cover additional use cases, in particular acting as a Data Abstraction Layer via it's web service functionality.” – Enterprise Architect, Asurion
- 19. 19 6. Location-agnostic architecture for multi-cloud, hybrid acceleration Optimizes costs by migrating data, applications, and analytics workloads to cloud without impacting the business Enables creation of hub architecture to support integration of data across mixed workloads. End-to-end management of migrations/promotions and continuous delivery processes. …enables cloud adoption Impressively quick turn around time to "unlock“ data from additional siloes and from legacy systems - Few vendors (if any) can compete with Denodo's support of the Restful/Odata standard - both to provide data (northbound) and to access data from the sources (southbound).” – Business Analyst, Swiss Re
- 20. 20 Modern Data Virtualization Data Virtualization enhanced with data management, automation and AI ➢ Delivers data more quickly than direct queries ➢ Leverages AI to accelerate performance and enhance the user experience ➢ An active data catalog to explore and govern data in real time ➢ Empowers data scientists with an integrated data science notebooks ➢ Flexible support for hybrid and multi-cloud architectures ➢ Employs automation to speed cloud deployment and management ➢ Leverages SSO and fine grain permissions to secure data assets
- 21. 21 Benefits of Using Data Virtualization Easier & faster access to trusted data • 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.
- 22. 22 Benefits of Using Data Virtualization Faster, cheaper, simpler, easier to secure and govern • 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 being 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.
- 23. 23 Data Virtualization use cases From Data Storage & Management, to Data Consumers, going through Data Governance & Security Decision (Real time) Single View (Customer 360) Agile BI (Self-service) Data Science (ML & AI) APPS (Mobile & web) Mergers & Acquisitions Data Marketplace Compliances (IFRS17, GRC) Data Security APIfication (& SQLification) Unified Data Layer Agility & Simplicity Real-time Delivery Data Abstraction Zero Replication Data Governance Sophisticated Optimizations Logical Data Warehouse/Lake Big Data Fabric Hybrid Data Fabric Data Integration Data Migration Refactoring & Replatforming Data Consumption Data Storage & Management Data Governance, Manipulation & Access Sales HR Executive Marketing Apps/API Data Science AI/ML
- 24. Denodo Standard
- 25. 25 Start with Denodo Standard for Data Virtualization, Expand to Data Management with Denodo Platform Start with data virtualization and grow into a Logical Data Fabric by adding the Data Management capabilities of Denodo Platform Data Virtualization (Denodo Standard) Logical Data Fabric (+Data Management) (Denodo Platform)
- 26. 26 Denodo Standard 8.0 Architecture
- 27. DENODO WEBINARS Product Demonstration Shehan Xavier Sr. Sales Engineer, Denodo
- 28. 28 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
- 29. 29 Denodo Standard 8.0 Demo
- 30. Key Takeaways
- 31. 1. Data architectures are getting more complex, more diverse, and more distributed 2. Traditional data integration and management approaches are too expensive, slow and complex 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 and data services to centralized data governance and compliance 5. Denodo Standard is the best entry level option, cheaper, easier to use and to acquire. Key Takeaways
- 32. Q&A
- 33. 33 Next Steps Try Denodo Standard today for free! www.denodo.com/free-trials GET STARTED TODAY
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