Copyright © 2014 Oracle and/or its affiliates. All rights reserved. Enterprise Data Management for...

Copyright © 2014 Oracle and/or its affiliates. All rights reserved.

Enterprise Data Management for Utilities Business Analytics

Martin DunleaSenior Director Utilities IBU, Oracle

Joe ZhouChief Technology Officer, Xtensible Solutions


Safe Harbor StatementThe following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.


Program Agenda

1. Introduction and Overview2. Building Data Management Core Competencies3. Oracle Utility Data Management Solution – A Standards-based Approach

for Utility Enterprise4. Roadmap5. Q&A


What Does Big Data Mean?

VOLUME VELOCITY VARIETY VALUE

SOCIAL

BLOG

SMARTMETER

101100101001001001101010101011100101010100100101

DEVICESSENSORS

What is the key difference in managing this data now?

Volume, Velocity, Variety, Value

These characteristics challenge most utility’s existing architecture, tools, staffing

competency and business processes!


Top Performing Companies Use Analytics to Drive Business Performance

Source: Oracle Study 2013 – “Utilities and Big Data: Accelerating the Drive to Value”

However, in utilities …


What Can We Do With the Data?Potential Use Cases – Sample List Only

Fault Analysis

Asset Planning

Asset Optimization

Load Forecasting

Financial Forecasting

Retail Customer Analytics

Price Elasticity

Power Quality

Risk Analysis

Event CorrelationTariff Analysis

Customer Sentiment Analysis

System Condition Analysis

Asset Failure Analysis

Predictive Maintenance

Predictive Customer Modeling

Load Balancing

Outage Analysis

Demand Response

Revenue Protection


Analytics are Fundamental to Improving and Sustaining Utility Business PerformanceImprove…

Customer Satisfaction

Targeted Interactions

Segmentation-driven marketing offers

Proactive alerting

Personalized communication

ReliabilityMore Effective

Monitoring and Proactive Maintenance

Asset management

Transformer load management

Operational Efficiency

Better Planning and Execution

Employee utilization

Revenue assurance

Optimized field work

SafetyUnderstanding and

Mitigating Hidden Risks

Reducing public safety hazards

Vegetation management

Field work management

Oracle helps your utility transform into a data driven organization.


The New Utility Enterprise Paradigm

IEC SG3 Smart Grid Architecture Model (SGAM)

•Utility Enterprise is faced with the integration of Information Technology (IT), Operational Technology (OT) and Communications Technology (CT)

•Utility systems are extending into the field devices through ICT to enable much more dynamic and granular operations.

•The needs to drive interoperability and intelligence (both centrally and distributed) are rising rapidly.

•Standards are being developed to address the needs across all domains and layers


Enterprise Data Management Framework

EDM Vision & Strategy EDM Governance EDM Core Processes EDM Organization EDM Infrastructure

Enterprise Vision & Strategy Enterprise Architecture Enterprise Business & IT

Core ProcessesEnterprise Business & IT Organizations Enterprise Infrastructure

Vision

Mission

Strategy

Goals & Objectives

Value Propositions

Sponsorship

Stewardship

Policies, Principles & Tenets

Alignment

Structure

CSFs & KPIs

Structure (Virtual, Hybrid……)

Roles & Responsibilities

Functional Services

Business Value and Relationship Management

Information Architecture Blueprint Management

Integrated DM Platforms(DBMS, Content Mgmt, ETL, SOA, EII, Data Modeling, BI/DW, Big Data , MDM)

Knowledgebase and Repositories

Standards & Best Practices

Data Quality

Data Integrity

Data Security & Protection

Data Lifecycle Management

Data Movement

Semantics Management

Database Management

Master Data Management

Information Services

Services & Support


What is Enterprise Data Management?

All Forms of Data

Common Information & Object Model

IntegratedAnalysis

InsightTo Action

•The system must be able to capture, process, organize, and analyze all forms of data in order to meet existing business requirements and support discovery of new business opportunities.

•The system must be able to maintain relationships and enable navigation between different forms of data.

•The system must organize information to provide a single version of truth•The system must share analysis artifacts to provide a single version of the question.•Governance must be instituted to properly maintain information and analysis artifacts

•The system must be able to monitor for important events and initiate alerts.•Users must be able to drill down into information in order to perform analysis.•Whenever possible, user should be given insight and guided to take proper action.

•Analysis should be integrated into the user interfaces, devices, and processes such that users gain insight where and when they need it.

•Business analytics systems should be integrated with business processes in a way to automatically leverage the available analysis to optimize operational processes.

Source: Oracle GTM for Big Data


What is Enterprise Analytics?

Descriptive Analytics --- using historical data to understand the “what” through reporting, scorecard, and clustering, etc.

Predictive Analytics --- using current and historical data to predict the future through statistical and/or machine learning techniques.

Prescriptive Analytics --- using the results of descriptive and predictive analytics to make suggestions on decision options through optimization and automation.

What happened and

why did it happen?

What and when will it

happen?

Why it will happen and

what options to take?


The Lifecycle of Enterprise Data Management, BI and Analytics

Source: Oracle Information Architecture: An Architect’s Guide to Big Data.


Utility Data Integration, Management and Analytics Landscape

Protection & Control

Grid Operational

Analytics

Waveform

Telemetry

Events

Messages

Files

Engineering Analytics

Customer Analytics

Asset Analytics

Grid State Analytics

Databases

Complex Event

Processing

Enterprise Service Bus

Big Data Analysis & Integration


MDM

ODS

BDA

Enterprise Data Warehouse

EDW

Enterprise BI, DM, and

Visualization

Analytics Models

Data Integration

Analytical Process Latency

Data A

cquisition Latency

BDA – Big Data ApplianceODS – Operation Data StoreMDM – Master Data ManagementEDW – Enterprise Data WarehouseBI – Business IntelligenceDM – Data Mart

•Utility data sources and analytical needs are diverse and require a variety of technologies to work together.

•This architecture allows utilities to invest where business needs are today and grow as they evolve.

•Key to this architecture is a layer of common data and information to be interoperable and future proof.


Where to Start?

EDM Vision, Strategy & Business Case

Governance(People, Process and Organization)

People------

Analytics skill gap, culture shift in data

sharing

Process------

Control of data movement, quality, and protection

Organization------

CompetencyCenter as a core

function of business and IT

Technology(Big Data, EDW,

Data Models, Master Data, Integration, BI )

Big Data------

What is appropriate for

your needs? Walk before

run.

BI/EDW------

EDW Appliance,Models, BI tools

consolidation

Data Management

------


and data integration


An EDM Roadmap

• Business and IT alignment to manage data and information as assets to the enterprise

• Agree on core EDM value and capabilities

Strategize

• Architecturally significant use cases

• Business-driven and IT-enabled approach with future in sight

• Deliver business value in day one

• Integrated data management platform technologies

Pilot

•Control your data movement and data integration•Manage data fidelity with data model and master data management•Standardize BI/DW platform•Reengineering data sharing, access and analysis practices

Build

• A service platform both in resources and technologies

• Balance in central and de-central capabilities through EDMCC

• Data become assets to be managed

• Analytics as a function to business processes

Deliver


Product Definition: Oracle Utilities Data Model (OUDM) is a pre-built, standards-based data warehouse solution designed and optimized for Oracle database and hardware. OUDM can be used in any applications environment and is easily extensible. OUDM enables utilities to establish a foundation for business intelligence and analytics across the enterprise, allowing each business domain to leverage a common analytics infrastructure and pre-defined cross-domain relationships, driving unprecedented levels of intelligence and discovery.

Oracle Utilities Data Model (OUDM)


Oracle Utility Data Model - A Solution Framework

•Foundation Layer: where multiple source of data are merged and integrated into one version of truth, without consideration of how users will access them.

•Analytical Layer: where data and information are aggregated into ways to facilitate reporting, ad-hoc queries, and data analysis.

•Presentation Layer: where the results of reporting and analysis are shown to end users.

Derived Tables

FoundationLayer

AnalyticLayer

PresentationLayer

Oracle Utilities Data Model


What is OUDM Really About?

It is a logical model that represents utility common

semantics

Derived Tables

FoundationLayer

AnalyticLayer

PresentationLayer

Oracle Utilities Data Model

It builds the integrated data foundation for

advanced analytics

It is based on Oracle Communications

Data Model and IEC Common Information

Model (CIM)It represents the

Oracle BI/DW solution best practices for utility enterprise

It focuses on cross application data

entities and relationships

It can be used to drive systems

interoperability for utility enterprise

It can be used to meet master data

management challenges


Unifying Enterprise Capabilities for Utility Integration, Data Management and Analytics – using OUDM

Oracle Event Processing

Oracle SOA Suite

Hadoop/Flume/Hive and Oracle BD

Connectors

Oracle Master Data

Management

BDA

Oracle Exadataand EDW

OUDM

OBIEE, ODM, Oracle R

Enterprise

Analytics Models

ODI and Golden Gate

OUDM

OUDM

CIM/OUDM

CIM/OUDM

CIM/OUDM

Protection & Control

Grid Operational

Analytics

Waveform

Telemetry

Events

Messages

Files

Engineering Analytics

Customer Analytics

Asset Analytics

Grid State Analytics

Databases

Analytical Process Latency

Data Acquisition Latency

•Utility data sources and analytical needs are diverse and require a variety of technologies to work together.

•This architecture, using OUDM/CIM, allows utilities to invest where business needs are today and grow as they evolve.

•For utilities that are looking to establish the core competency around data management, Oracle is the right partner.


Implementation RoadmapTrain, Implement, and Transfer Knowledge

• Demonstrate the capability and maturity of the OUDM solution

• Choose a couple of use cases to show how to use OUDM/CIM to integration and analyze data from multiple sources

• Use appropriate technologies (ESB, ETL, BI, etc.) to show how these technologies work together to deliver business value

Demonstrate

• Focus on the immediate needs of a utility and deliver tangible results

• Provide hands on training and knowledge transfer to utility personnel

• Help establish sustainable methods, tools and infrastructure to meet future demands

Implement • Provide on-going support to utility team

• Work with strategic utility partners for the direction of OUDM future releases

• Deliver more packaged analytics and packaged integration.

• Expand to other enterprise technologies

Sustain


Summary

Why

• Utility industry is faced with tremendous challenges both internally and externally• Increased volatility • Fusion of IT, CT and OT

What

• Utilities must establish core competencies around data management and analytics in order to be more competitive, efficient and effective

• Utilities must do so proactively and strategically

How

• Data management core competencies around people, process and technology• Manage and use data and information as “assets”

Who

• Business and IT must partner together to build the core competencies• Engage strategic partners and leverage best practices and standards

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. Enterprise Data Management for...

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