Digital Data Hub The Digital Data Hub is a central data repository for raw and derived enterprise data. It may typically be an enterprise data lake. It includes real-time and batch-processing capabilities. IDF, as earlier stated, consists of the end-to-end data supply chain pipeline that enables this new digital master data. • Real-time processing Real-time detection • Predictive scoring Predictive models are Figure 9: Digital Data Hub of patterns in the data and event triggering are used to score data, delivering precise insights enabled, which in turn promotes prompt decision that facilitate informed decision-making Real-time Processing -making, enhancing the data lake’s processing based on quantitative logic and insights. Smart Data Preparation & Analytics Enrichment capability, insight generation and analytics. • Machine learning Machine learning leverages • Smart data preparation & analytics enrichment IDF processing capabilities to rapidly explore Real-time Query Data preparation is an iterative process for different permutations and generate the best exploring and transforming raw data into model for entity resolution and fuzzy data forms suitable for analytics enrichment, data matching. Machine learning is also leveraged Digital Data Hub (IDF) science experiments, data discovery and for intelligent data capture and curation, analytics. Analytics enrichment infuses digital profiling and data tagging to enhance Predictive Scoring data transactional information with attributes metadata management and data quality. that enable a 360-degree view of data. • Insights discovery Statistical and mathematical Machine Learning • Real-time query Real-time query capabilities methods are leveraged in order to provide both Insights Discovery facilitate insights discovery, data visualization descriptive and predictive analysis of data to and real-time decision support. facilitate query, analytics and decision support. Copyright © 2019 Accenture. All rights reserved. Meet Your Digital Master 27