A Logical Architecture is Always a Flexible Architecture (ASEAN)
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The document discusses the importance of a flexible data architecture that translates business needs into effective data and system requirements. It highlights the need for a user-driven, secure, and minimally disruptive design capable of integrating diverse data sources while ensuring data governance and compliance. Additionally, it emphasizes data virtualization as a key solution for enabling real-time access to data services without replication or relocation, ultimately improving decision-making and operational efficiency.
A Logical Architecture is Always a Flexible Architecture (ASEAN)
- 1. A Logical Architecture is Always a Flexible Architecture Chris Day Director, APAC Sales Engineering cday@denodo.com 4th Chief Digital Officer Asia Summit 3 June 2021
- 2. 2 www.cio.com The goal of data architecture is to translate business needs into data and system requirements and to manage data and its flow through the enterprise.
- 3. 3 Characteristics of an Effective Data Architecture • User-driven • Decision makers or data consumers should easily be able to access the data they need to meet business objectives • Secure • Security should built into modern data architecture, ensuring that data is available on a need-to-know basis as defined by the business. Also ensure regulatory compliance with legislation like GDPR • Minimal Disruption • Designed to accommodate and meet the changes required by either technology or business requirements • Elastic and adaptive • Support multiple types of operations (e.g., batch, stream), query operations, and deployments (e.g., on premises, public cloud, private cloud, hybrid)
- 4. 4 Common Reality of Enterprise Architecture Becomes Unmanageable & Brittle because: 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)
- 6. 6 Logical Architecture – Path to the Future Stop collecting, Start connecting
- 7. 7 Data Virtualization Architecture: Connect Not Collect
- 8. 8 Data Virtualization: Unified Data Integration and Delivery • Data Abstraction: decoupling applications/data usage from data sources • Data Integration without replication or relocation of physical data • Easy Access to Any Data, high performant and real-time/ right- time • Data Catalog for self-service data services and easy discovery • Unified metadata, security & governance across all data assets • Data Delivery in any format with intelligent query optimization that leverages new and existing physical data platforms Six Essential Capabilities of Data Virtualization
- 9. 9 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
- 10. 10 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.
- 11. 11 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
- 12. 12 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
- 13. 13 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
- 14. 14 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
- 15. Customer Case Study The Credit Agricole Story
- 16. 16 138,000 employees 50 countries 10th World’s Largest Bank Is part of the Crédit Agricole Group. World leader in Green, Social and Sustainable Banking Credit Agricole Story: Logical Data Lake Today CACIB’s architecture had • 1000+ data flows, dozens of domain specific data warehouses, terabytes of curated data processed yearly • 100s of business processes and 1000s of users worldwide Credit Agricole wanted a platform • To perform unified analytics spans its entire data infrastructure & eliminate data trapped in business silos • Create a universal data delivery layer without having to replicate data • Enable users to search and access the right data set via existing tools • Data governance framework allowing definition, management and security of data
- 17. 17 Siloed Data Ecosystem Enterprise Data Lake? Costly, Complex , Difficult to maintain Is Another Data Lake Really the Answer?
- 18. Target Unified Analytics Using a Logical Data Fabric Querying with user’s favorite tool from the semantic layer 3 1 … Finding the right data 2 Keyword search Metadata Logical Layer API’s API’s Physical Layer
- 19. 19 The Logical Data Fabric Advantages for CACIB 1. Logical Data Warehouse : Gather data from multiple data stores : E.g. : Steering Analytics project, Counterparty Risk data Integrity Front to Back, Market Data, etc… 2. Operational analytics : capacity analytics tool to operational data sources (API, Databases, etc) in order to have the real-time data E.g.: Front Office trading system real-time analytics by logical merging of multiple instances worldwide 3. Data services : capacity to publish an API/ODBC connection for subscriber to consume data E.g. : IT Financial data APIs 1. Domain data prepared and published as Data Services via API/ODBC/Etc… connectors 2. Seamless connectivity with data management system (including Enterprise data calatog) 3. Data security integrated and governed Application/process level component - Aimed to serve a specific process or use cases as a middleware layer for data integration or data push Domain level component (Hub) – Data Centric Initiative : Aimed to democratize the data sharing/publication between different business departments
- 20. 20 Key Takeaways A logical architecture: • Allows adoption of newer technologies without impacting business users. • Improves decision making and shortens development cycles. • Eliminates data silos unified view of company data from multiple repositories without the need to replicate. • Broadens use existing data sources improving their ROI & value • Improves governance and metadata management to avoid “data swamps”
- 21. Next Steps
- 24. Thanks! www.denodo.com info@denodo.com © 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. 24