Delivering Analytics at The Speed of Transactions with Data Fabric
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The document discusses the importance of data as a critical business asset and the challenges organizations face in utilizing data insights effectively due to its dispersion across multiple repositories. It proposes a data fabric approach that integrates disparate data sources in real-time, offering a solution for improved analytics and decision-making. Recommendations include leveraging data virtualization for faster deployments, focusing on real-time data initiatives, and establishing dedicated data fabric teams.
Delivering Analytics at The Speed of Transactions with Data Fabric
- 1. Delivering Analytics at the Speed of Transactions with Data Fabric Noel Yuhanna Vice President, Principal Analyst
- 2. Feb 2022 Noel Yuhanna Vice President, Principal Analyst Delivering Analytics At The Speed Of Transactions With Data Fabric
- 3. 3 3 © 2021 Forrester. Reproduction Prohibited. © 2022 Forrester. Reproduction Prohibited. Data has become the most critical asset for any business to succeed.. Increase Revenue Retain Customers Deliver new products and services Enable Innovation 51% Commercializing data! Improve customer experience Expand markets And more …
- 4. 4 4 © 2019 FORRESTER. REPRODUCTION PROHIBITED. 91% report that improving the use of data insights in decision making is challenging. 85% want to improve their use of data insights in their decision making. Source: Forrester Analytics Global Business Technographics® Data And Analytics Survey, 2019
- 5. 5 © 2022 Forrester. Reproduction Prohibited. Today data is spread across multiple repositories and locations that creates new data challenges… 5G Smart Devices Edge Computing IoT Sensors Driverless Cars Robots Social media SaaS DaaS providers Data lakes/DW Legacy Apps Data Cloud Edge OnPrem
- 6. 6 Legacy data architectures are geared towards slower data movement between analytics platform which impacts business success…
- 7. 7 Data Latency – Is slowing down new initiatives! Transactional Analytical Operational Data loading is slow Delayed Execution Downtime impact Old architectures
- 8. 8 © 2022 Forrester. Reproduction Prohibited. Positive Slowing down insights can impact decisions and can even by harmful to the business …. Business value Time to action Data originated Analytics performed Insights gleaned Action taken Outdated insights Impotent or harmful actions Negative Decision made Poor decision Traditional ETL/DI approaches
- 9. 9 9 © 2019 FORRESTER. REPRODUCTION PROHIBITED. 178% more likely to grow revenue 2.5 times more likely to grow revenue at 20% or more. Base: 1,376 global data and analytics decision Source: Forrester Analytics Global Business Technographics® Data And Analytics Survey, 2020 Insights-driven firms that take accurate and quicker decisions are …
- 10. 10 Businesses need is a new approach to connect data silos in real-time to support various applications, insights, and analytics.
- 11. 11 © 2022 Forrester. Reproduction Prohibited. Which of the following are the most important components of your organization's plans for data, data management in the next 12 months? Data integration, quality, MDM, governance are most important components for organizations … Source: Forrester’s technographics data 2021
- 12. 12 12 © 2019 FORRESTER. REPRODUCTION PROHIBITED. Data lakes, EDW haven’t been able to address real-time insights, all data analytics or deal with multiple workloads… Streaming Sources Trans/Oper. Data External Source Click stream Log stream Operational OLTP Partners SaaS Data Lake Data Warehouse Data Discovery BI/Analytics Usage/Use Case/Delivery Integration Enrichment Metadata Security Governance Classification Processing Quality Multiple Data Lakes Predictive Analytics Systems of Insight Data Science Customer intelligence
- 13. 13 13 © 2019 FORRESTER. REPRODUCTION PROHIBITED. Data virtualization/ Data fabric overcomes the gaps by leveraging any data in real-time and in a self-service manner … Streaming Sources Trans/Oper. Data External Source Click stream Log stream EDW OLTP Partners SaaS Data Lake Data Warehouse Data Discovery BI/Analytics Usage/Use Case/Delivery Integration Enrichment Metadata Security Governance Classification Processing Quality Multiple Data Lakes Predictive Analytics Systems of Insight Data Science Real-Time Analytics Data Virtualization / Data Fabric
- 14. © 2021 Forrester. Reproduction Prohibited. DEFINITION FORRESTER “Dynamically orchestrating disparate data sources intelligently and securely in a self-service and real-time manner and leveraging various data platforms to deliver integrated and trusted data to support various applications, analytics, and use cases” What is a Data fabric? © 2021 Forrester. Reproduction Prohibited.
- 15. 15 15 © 2021 FORRESTER. REPRODUCTION PROHIBITED. Forrester’s Enterprise Data Fabric Reference Architecture Data Security Data Governance Metadata/Catalog Data Processing Data Quality Data Lineage Data Management Global Distributed Platform, In-memory, Embedded, Self-Service, APIs, Global Data Access Data Modeling, Preparation, Curation, Graph Engine Data Discovery Transformation, Integration, Cleansing Data Orchestration/Data Virtualization Ingestion, Streaming, Data movement Data Ingestion/Streaming Data Virtualization Data Platform – Processing Data Processing/ Persistence Hadoop NoSQL Spark Data Lake EDW/BDW On-premise Cloud Data Sources Policies AI/ML AI/ML AI/ML AI/ML AI/ML AI/ML © 2021 Forrester. Reproduction Prohibited.
- 16. 16 16 © 2021 FORRESTER. REPRODUCTION PROHIBITED. Data fabric delivers integrated, trusted and real-time data to support your cloud data strategy for multiple personas Systems of Engagement Systems of Record Data Fabric Sematic Layer Systems of Transactions Data Sources Catalog Quality Metadata Security Governance Models Transformation Integration Developers Data scientists Data engineers Security analysts Business users Data analysts Data Architects Enterprise architects AWS Azure GCP © 2022 Forrester. Reproduction Prohibited.
- 17. 17 © 2022 Forrester. Reproduction Prohibited. Expanding data fabric Use cases…. •Customer 360 — personalization •Customer intelligence — for upsell/cross-sell, targeted marketing •IoT Analytics •Risk analytics •Data science •Microservices Applications •Fraud detection •Industry specific use cases •And others…
- 18. 18 © 2021 Forrester. Reproduction Prohibited. Recommendations Leverage data virtualization to accelerate data fabric deployments. Focus on real-time initiatives which is the sweet spot for data fabric. Create a data fabric team to succeed – Enterprise architects, data architects, developers, data engineers, data security, business analysts. Keep security in mind from start when supporting various data sources especially when dealing with sensitive data. Leverage data fabric solution to help automate integration, deliver self-service capabilities, support trusted and real-time customer data initiatives.
- 19. 19 © 2022 Forrester. Reproduction Prohibited. Thank You. Noel Yuhanna Vice President, Principal Analyst
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