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APTAtech: Transportation Technology Conference

September 15-18, 2019 / Columbus, Ohio

Alameda-Contra Costa Transit District

September 16, 2019

Big DataChallenges, Opportunities, and Initiatives

Agenda

• Intro to Alameda-Contra Costa Transit District

• Rapidly Changing Public Transit Domain

• Assessing the Agency Core Mission and Technology Landscape

• Big Data

• Challenges

• Opportunities

• Initiatives

• Takeaways

AC Transit at a Glance

• Serves 13 Cities and 8 Unincorporated Areas

• Directly Elected Board

• Alameda and Contra Costa Counties

• Facilities:3 – Oakland1 – Emeryville1 – Hayward1 – Richmond

• Service Across 3 Bay Area BridgesDumbartonSF–Oakland San Mateo

All About Numbers

Daily

169,000

Daily service hours

5,800(weekday)

16 other bus systems

25 BART stations

6 Amtrak stations

3 ferry terminalsAnnual

52,300,000

Paratransit

771,000(annual)

RIDERSHIP

Bus lines

160

SERVICE

Bus stops

5,500(approximately)

Annual service miles

20.4 million

CONNECT WITH

Transbay daily

14,500

Public Transit Domain

• OEMs• Marriage of HW and SW• Bus is becoming an integration platform• Automation and Electrification

• Operators• Embracing the new reality of sharing• Relying on technology• Transit to Mobility providers

• Riders• Customer Experience• Multimodal Trips are norm

Riders

Operators

OEMs

Data is the new oil!

• Business Case - Media rich applications are becoming norm with real-time video, voice, maps and images

• Data is the most important component for any transit agency

• Public vs Private Data Domains

• Digital Platforms are becoming relevant to support IoT

• Data Driven Decisions

ConnectedVehicles

RidersCities and Counties MPO

CAD/AVL

Technology Landscape

Big Data Challenges:

• Complexity due to Volume, Variety and Velocity• Data from internet connected sensors, videos, social media and mobile applications,

• How to quickly clean, qualify and facilitate ?

• Complexity due to numerous Data Sources for Big Data

• Integrating unstructured Big Data with Structured Organizational Data. • Unstructured data shouldn’t become a silo of its own

• Should be cleaned and qualified

• Facilitate Advanced Analytics, Artificial Intelligence, Real Time Analytics and more

• Business needs a complete and accurate data, with complete lineage – Big, Large or Small.

Big Data Challenges

Data Governance - The orchestration of people, processes, and technology to manage critical data assets by using roles, responsibilities, policies, and procedures to ensure the data is accurate, consistent, secure, and aligns with overall organizational objectives.

• More than 30 small and big applications, grew over the period of time across ACT. (HASTUS, ELLIPSE, CAD/AVL, PeopleSoft, etc)

• Complex infrastructure with Applications hosted on-premise, data-centers and cloud.

• Several sources-of-truth.

• Additional new applications bringing very large volume of data (Big Data).

• Transit Organizations generating highly useful data, both for public and private domain.

• Very high demand of Quality and Reliable Data

Data Integration Complexity

Enterprise Application Architecture Hastus

Planning Scheduling

Bid/BidWeb Daily Crew/Vehicle

PeopleSoft

HCM

Finance

HP 3000: Opera and Whoopi

Operators Timekeeping System (OTS)

Transportation Information System (TIS)

Ellipse: Asset Management Systems

Vehicle Maintenance Facilities

Inventory Materials

Office 365: Emails, SharePoint, Office

Customer Relations System(CusRel): Complaints and commendations

Training Application: Internal trainings supportAuto Request System: Non revenue vehicle reservation

FileBound: Online document management system

WorkLog Application: Work requests for facilities and bus stops

RestRoom Finder: Rest rooms catalog for operators and road supervisons

Esri ArcGIS: Geographic Information Systems

Granicus: Board agenda, meeting, live streaming and recording support

Kronos TimeLink: Employee time clock for Maintenance employees

NeoGov: Recruiting system

GovDelivery: Customer alerts system

Road Calls Application: Revenue fleet field maintenance

FleetWatch: Revenue vehicles fuel and oil usage tracking

Genfare: Cash fare collection system

Clipper: Electronic fare collection system

SalesFore: External affairs and marketing support

Smanage: Help desk incidents and responses

APC: Automatic passenger count

WordPress: Public website content management system

Warranty Application: Equipment and parts warranty support

RMIS: Risk management and claims

Mobile website: Mobile application for the public website

Vehicle Locator: Live vehicle status and locations

NextBus: Real-time schedules and predictions online and at bus stops

API: GTFS and GTFS Real-Time Aps for external smart apps

AC Reports: District standard reports from Enterprise Database

PowerBI: Analytics tool for Departments

KPI Dashboard: District standard Key Performance Indicators

Public KPI Dashboard: Public Key Performance Indicators and lobby display

Bus Pullouts: Bus pullout and schedule information display

Kantech IntraPass System: Security and badge systems

Traka Key Box: Key security system

Service Ware: Operator uniform request system

SalesForce Terminal Sign: Schedules display at the terminal

Visual Directory: Office directory with floor plan

CAD/AVL (Upgrade from Orbbital to Clever Devices)

Computer Aided Dispatch

Radio / VOIP

AVL Analytics

Enterprise Database Platform

Application Databases

Data Warehouse

• Advanced Integration Architecture by leveraging some of the latest tools and technologies. Few of these under review are• - Azure SQL Services and API Management, MuleSoft, Kafka, etc.

• Better Master Data Management and Data Quality Management to ensure the core data is universally defined, qualified and validated

• Define and establish Data Lakes, with Global Security and common access methods.

• Finally, adapt to a comprehensive Corporate Data Governance across the organization.

High Level Approach

Source Applications and Transactional Data

Unified Integration and API Management

DQM as team effort between Data Stewards, Departments and IT

Integrated, Qualified and Aggregated Data Warehouse defined by Business

Logical Interface for Integration of all Data Sources, providing Secure and Simplified view of Enterprise Data

Rich set of Analytics and Visualization tools, governed by Global Security Model

Data Access Layer - Secure(Reporting Tools)

Data-warehouse

Logical Layer - Secure LogicalData Marts

Data Marts

Unstructured Data

Master D

ata Managem

ent

Dat

a G

over

nanc

e

CleverCAD/AVL

PS HASTUS Ellipse other other

Controlled, Direct

Connections

Data Quality Management(validate and qualify)

Data Ingestion / Integration Layer(API Management)

Conceptual Data Architecture

Daily PayDuty &

BidGL

BalanceAccounts

Sign Ups

Date

Duty

Route

Operator

Division

Trip

HASTUS PeopleSoft HR PeopleSoft FIN

• Visualizations using Power BI and Tableau

• Advanced Analytics with drill-to-detail, historical data and slice-and-dice capability

• Integrated and connected Dimensional Modelling

• Master Data Management Processes

• Data Quality Management Processes

Service Operations Costing Module (SOCM)

SOCM – Case Study

Goal:

Ensure financial resources are utilized efficiently and effectively

Solution:

Establish systematic approach for producing a Total Cost Estimate of Service Operations by Route

ZEB DIMA – Case Study

• Integration of disparate energy systems

• Advanced Analytics with drill-to-detail, historical data and slice-and-dice capability

• Master Data Management Processes

• Energy Optimization Engine using ML/AI

Zero Emission Bus – Data Integration, Management and Analytics (DIMA)

Takeaways

• Data is eating the world!• Play with AI/ML technologies

• Point solutions• Business solutions

• Embrace Digital Disruption• Cannot ignore Cyber Security and Privacy

• Data Governance and Framework• Data Science – New Skills are required• Collect – Organize – Analyze

• Pick a POC