Your Data is Waiting. What are the Top 5 Trends for Data in 2022? (ASEAN)
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The document discusses the top five data trends for 2022 presented during a Denodo lunch and learn event, including the rise of data fabric technology, decision intelligence for enterprise support, data mesh architectures, composable data and analytics, and the emergence of small and wide data analytics. It emphasizes the importance of data virtualization and self-service data marketplaces in modern data management. The conclusion highlights the agility and cost-effectiveness of implementing a global data strategy independent of traditional integration techniques.
Your Data is Waiting. What are the Top 5 Trends for Data in 2022? (ASEAN)
- 1. DENODO LUNCH AND LEARN ASEAN Your Data Is Waiting. What Are the Top 5 Data Trends in 2022?
- 2. Speakers Elaine Chan Regional Vice President, ASEAN & Korea Chris Day Director, APAC Sales Engineering
- 3. Agenda DENODO LUNCH AND LEARN ASEAN 1. 5 Data Trends for 2022 2. Conclusion 3. Q&A 4. Next Steps
- 4. Trend #1 Data Fabric Will Become the Foundation for the Distributed Enterprise
- 5. 5 Source: “Forrester Study, Total Economic Impact of using DV, November 2021” Data Fabric technology takes data virtualization a step further by automating data management functions using artificial intelligence / machine learning and providing additional semantic capabilities through data catalog, data preparation, and data modelling.
- 6. 6 Data Fabric A data fabric is an architecture pattern that informs and automates the design, integration and deployment of data objects regardless of deployment platforms and architectural approaches It utilizes continuous analytics and AI/ML over all metadata assets to provide actionable insights and recommendations on data management and integration design and deployment patterns. This results in faster, informed and, in some cases, completely automated data access and sharing Strongly supported by both Gartner and Forrester Data Fabric Net Compounds Customers Products Claims RDBMS/OLTP Traditional Analytics/BI Data Lakes Cloud Data Stores Apps and Document Repositories Flat Files Third Party Legacy Mart Data Warehouse Mart ETL ETL XML • JSON • PDF DOC • WEB
- 7. 7 Logical Data Fabric Value & Capabilities Delivered Value of Logical Data Fabric § Unified data access across all data storage locations § React quickly to new data and business requirements § Strategic implementation of information landscape § Leverage efficiencies of cloud environments § Digital transformation and modernization without business disruption § Accelerate new virtual data models for continually changing requirements Capabilities Delivered: § Modern, future proof information landscape § Abstract data consumption from data storage and processing § Easy, unified access to all data in a standard interface § Support self service and governance
- 8. Trend #2 Decision Intelligence Will Make Inroads for Enterprise-wide Decision Support
- 9. 9 Source: “Gartner Peer Insights, November 2021” Data Virtualization can be used to create virtualized and integrated views of data 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 Data Virtualization: Unified Data Integration and Delivery A logical data layer that provides high-performant, real-time, and secure access to integrated business views of disparate data across the enterprise. Data Abstraction: Decoupling applications and data usage from data sources and infrastructure Zero Replication, Zero Relocation Physical data remains where they are Real Time Information Most reporting and analytical tools can easily connect for real time data Self Service Data Marketplace A Dynamic Data Catalogue for self-service data discovery and data services available in the virtualization layer Centralized Metadata, Security & Governance: Manage access across all data assets in the Virtualization layer for enterprise data security and supports dynamic data anonymization Location-agnostic Architecture For hybrid and multi-cloud acceleration
- 11. 11 with augmented AI/ML-driven decision support systems Enterprise-wide Decision Support
- 12. 12 Enterprise-wide Decision Support Value & Capabilities Delivered Value Delivered: § React quickly to new data and business requirements § Reduce IT & infrastructure costs & drive efficiencies § Ease of organizational decisions based on all operational and historical data Capabilities Delivered: § Modern, future proof approach to data management and capabilities § Prevent lock in from visualization and analytical tools § Single view and implementation of governance and security across all data § Unified access to all data across cloud, on-premise and software as a service
- 13. Trend #3 Data Mesh Architectures Will Become More Enticing
- 14. 14 What Is a Data Mesh? § The Data Mesh is a new architectural paradigm for data management § Proposed by the consultant Zhamak Dehghani in 2019 § It moves from a centralized data infrastructure managed by a single team to a distributed organization § Several autonomous units (domains) are in charge of managing and exposing their own “Data Products” to the rest of the organization. § Data Products should be easily discoverable, understandable and accessible to the rest of the organization.
- 15. 15 What Challenges is a Data Mesh Trying to Address? 1. Lack of domain expertise in centralized data teams § Centralized data teams are disconnected from the business § They need to deal with data and business needs they do not always understand 2. Lack of flexibility of centralized data repositories § Data infrastructure of big organizations is very diverse and changes frequently § Modern analytics needs may be too diverse to be addressed by a single platform: one size never fits all. 3. Slow data provisioning and response to changes § Requires extracting, ingesting and synchronizing data in the centralized platform § Centralized IT becomes a bottleneck
- 16. 16 Virtual Data Mesh Consumers Data Science Machine Learning Artificial Intelligence Mobile Applications Predictive Analytics Business Intelligence Unified Data Security Abstraction Layer Universal Access Self-Service Data Catalog Data Domains
- 17. 17 Denodo Platform Architecture DATA CATALOG Discover - Explore - Document DATA AS A SERVICE RESTful / OData GraphQL / GeoJSON BI Tools Data Science Tools SQL CONSUMERS DATA VIRTUALIZATION CONNECT to disparate data in any location, format or latency COMBINE related data into views with universal semantic model CONSUME using BI & data science tools, data catalog, and APIs Self-Service Hybrid/ Multi-Cloud Data Governance Query Optimization AI//ML Recommendations Security LOGICAL DATA FABRIC SOURCES Traditional DB & DW 150+ data adapters Cloud Stores Hadoop & NoSQL OLAP Files Apps Streaming SaaS
- 18. Trend #4 Organizations Will Embrace Composable Data and Analytics to Empower Data Consumers
- 19. Where Is My Data? Web Content Big Data Application Graph Database Relational Databases Cloud Storage (S3, ADLS, GCS) JSON/XML Files SaaS Applications Flat Files Data Warehouse Excel Spreadsheets ?
- 20. 20 DENODO LUNCH AND LEARN ASEAN Data Marketplace Cloud Storage (S3, ADLS, GCS) SaaS Applications Relational Databases JSON/XML Files Flat Files Data Warehouse Excel Spreadsheets Graph Database Data Virtualization Data Catalog Big Data Application
- 21. 21 DENODO LUNCH AND LEARN ASEAN Empowering Your Enterprise with a Self-Service Data Marketplace DATA C ATA LOG D EM O
- 22. Data as a Service Data as a Service 3 Enrich the data set Look for a data set Understand the data Publish & share the data set Demo 1 2 4 Business User & BI Analyst
- 24. 24 Benefits for End Users Increased Agility and Better TTM § Single place to access any data § Hides complexity of back-ends § On-prem vs. Cloud § Formats and protocols Trust § Consistency of results regardless of access method § Documentation, lineage, governance, etc. Reusability § Access to same data and metrics from anywhere as logic is not coded in a BI tool § Any data available in multiple standardized formats: SQL, REST, OData, GraphQL, etc.
- 25. Trend #5 Small and Wide Data Analytics Will Begin to Catch On
- 26. 27 Modern Data Management Reference Architecture Reporting Analytics Data Science Data Market Place Data Monetization AI/ML iPaaS Kafka ETL CDC Sqoop Flume Raw Data Zone Staging Area Curated Data Zone Core DWH model Data Warehouse Data Lake Data Virtualization Platform Analytical Views Data Science Views λ Views Real-Time Views DWH Views Hybrid Views Cloud Views Universal Catalog of Data Services Centralized Access Control Enterprise Data Fabric DATA VIRTUALIZATION
- 27. 29 Small & Wide Data Analytics Value & Capabilities Delivered Value Delivered: § Unified data access and metric management § Decisions based on all data assets, not just easily accessible ones § Apply consistent governance & security § React quickly to changes in different lines of business Capabilities Delivered: § Dynamic platform for continuing changes to business and market requirements § Future proof data and analytics landscape § Single view and implementation of governance and security across all data § Unified access to all data across cloud, on-premise and software as a service
- 28. DENODO LUNCH AND LEARN ASEAN Conclusion
- 29. 31 A Global Modern Data Strategy… For the first time, a technology that allows you to define and implement a data management and data delivery strategy: § Independent from the sources where you store and process your data § Independent from the consuming applications § Independent from the location of the deployment § Can enforce security and access policies § More agile and at a lower cost than traditional data integration techniques
- 30. DENODO LUNCH AND LEARN ASEAN Next Steps
- 31. 34 Get Started Today Try Denodo for a Test Drive with a 30-day free trial in the cloud marketplaces CHOICE Under your cloud account SUPPORT Community forum AND remote sales engineer OPPORTUNITY 30 minutes free consultation with Denodo Cloud specialist denodo.link/drive22
- 32. Denodo Is Once Again a Customers’ Choice in 2022 Gartner Peer Insights™ “Voice of the Customer”: Data Integration Tools READ FULL REPORT: denodo.link/peer22 The Gartner Peer Insights Customers’ Choice badge is a trademark and service mark of Gartner, Inc., and/or its affiliates, and is used herein with permission. All rights reserved. Gartner Peer Insights Customers’ Choice constitute the subjective opinions of individual end-user reviews, ratings, and data applied against a documented methodology; they neither represent the views of, nor constitute an endorsement by, Gartner or its affiliates.
- 33. DENODO APAC WEBINAR SERIES The Value of Data Virtualization in a Data Mesh 17 March • 1.00pm SGT Mike Ferguson Managing Director Robin Tandon Director of Product Marketing REGISTER NOW: denodo.link/DM22 ACCESS REPORT: denodo.link/DM22R
- 34. 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.