Electricity Asset Management Plan 2019-2029
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Vector Limited://
Tools Used (WiP) Figure 4-2 below depicts the data and analytics platform (D&A) logical architecture. As noted in Section 4.1.13, Vector has a digital infrastructure and data platform strategy & roadmap which will implement an integrated, flexible and modern data & analytics platform which can scale to meet the increasing needs of data volume, velocity, veracity and variety.
Figure 4-2 Logical Architecture Breakdown • Data Sources – Data is collected from all core Vector systems as well as external data providers which include public and private subscription data sets. • Data Movement – Data is extracted or loaded from the data sources in a managed fashion. It is organised, integrated, and loaded into the Data Lake and/or Enterprise Data Warehouse. This can be performed in near real-time or in batch processing as required. • Shared Data Platform (Data lake) – Used for storing high volume and diverse data sets (aka Big Data). The technology allows more flexibility and greater processing power and performance than traditional systems. • Execution tier – Responsible for transforming raw data into meaningful and easily understood information. • Consumption tier – Responsible for providing data visualisation, reporting and analytics tools to all data consumer groups within the organisation and also trusted external parties. • Services tier – Responsible for integrating/sharing analytical data with digital systems and external organisations through a common platform and method (API). • Metadata management, security and governance – Supports data governance and security by classifying (security, sensitivity, domain) & cataloguing data across multiple repositories.
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