Implementing a Big Data Strategy PRASA Passenger Rail Agency of South Africa

Transcription

1 Implementing a Big Data Strategy PRASA Passenger Rail Agency of South Africa MarkLogic World 2016 San Francisco

2 AGENDA Agenda Introduction About the customer Project Goals Challenges The Solution Demo

3 WHO AM I Introduction Alexander Deles CEO, EBCONT More than 20 years experience in IT MarkLogic Partner since 2011 EBCONT delivered more than 20 MarkLogic projects successfully

4 WHO WE ARE EBCONT group EBCONT is a leading Austrian provider of IT, communication and personnel services. Established in 2000, its founder Rupert Weissenlehner still privately owns the company. Initially positioned as a pure IT service provider, EBCONT used its first ten years of systematic development and stable growth to consolidate a corporate structure in Employees 550+ Turnover 52 Mio. Euro Owner Rupert Weissenlehner Focus IT, Communication Award: EBCONT is MarkLogic Partner of Excellence!

5 THE CUSTOMER The Customer

6 THE CUSTOMER Passenger Rail Agency of South Africa PRASA BE MOVED Name Industry Founded Headquarter Revenue Employees PRASA Passenger rail 1990 (as SARCC) Hatfield, Pretoria ZAR 4.2 billion (USD 275 Mio.) 500,000 (whole group)

7 PROJECT GOALS Project Goals

8 REASON TO ACT Digital Evolution

9 GOALS Overall Goals Create a Data Strategy Define a data centric enterprise IT architecture Define a data centric interface strategy and workflow for all IT systems Deliver Proof-of-Concept Implement Reference Implementation Reference Infrastructure

10 GOALS Goals 360 degree overview Standardize reporting Improve quality of service Fraud detection Geo spatial data / heat maps Point-in-Time analysis Alerting Root cause analysis Virtualize data Ease of use use everywhere with: Desktop PC Tablet Smartphone

11 GOALS Why Data Virtualization? CRM, Web CMS, Marketing, Ticketing, Contact centers, HR, Counters, Incident Management, Schedules, etc.

12 Challenges

13 CHALLENGES Challenges Variety of data Different systems and formats for the same purpose e.g. more than one incident management system Data quality Different coverages Data linkage Different languages English Africans

14 DATA Input Data Ticket Sales Train Movement Data Tracks Incident Management Stations Fuel Prices Weather Data Documents Twitter Work Shift Data

15 PERSPECTIVES Different Perspectives Executive Org. Performance Exploration Find patterns Improvements Near real-time data Reporting Ad-hoc insights Operations Root cause analysis Data streams Alerting

16 Solution

17 PROJECT SETUP Project Streams Quarter 1 Quarter 2 Quarter 3 Data strategy stream Prototyping stream Reference implementation stream Reference infrastructure stream

18 INGREDIENTS Ingredients 1 CONCEPT 2 APPROACH 3 TECHNOLOGIE Bi-Modal IT Data Centric Next Generation Database Enterprise NoSQL For all your data! Schema-agnostic Massive scale Query and search Analytics Application services Semantics Geo Spatial

19 BI-MODAL IT Bi-Modal IT

20 ARCHITECTURE So - What s the plan?

21 PROVEN PRACTICE: EBCONT S DATA SERVICES HUB CONCEPT Short Cycles Business- and Customer- Centric Dashboard Search Apps Streams Applications Business Centric BI-MODAL IT Agility Reliability Roles and Governance System n Data Centric Approach Integration Pattern (Template) Initial Data Load Updates API System 1 API Data Integration Data Transport System 2 API API Poly-structured Content Government Grade Security Extraction Semantics Geo-spatial Data Intelligence Data Quality System 3 API System 4 API Flexible IT Data Centric Stable IT IT Centric

22 INFRASTRUCTURE Scalable Reference Infrastructure ETL 1 ETL 2 ESB 1 MarkLogic1 DATA LAYER VMS ESB 2 MarkLogic2 MarkLogic3 MarkLogic4 VMH1 VMH2 VMH3 VIRTUALIZATION CLUSTER Firewall Storage SVN Nexus APP 1 APP 2 Admin DB VMH4 VMH5 Load Balancer MarkLogic5 Technology stack Apache Loadbalancer Red Hat Enterprise Linux VM Ware Cluster NETAPP (Storage) HP (Server) Astaro (Firewall, virtualized)) Zabbix (Monitoring) Veeam (Backup)

23 HOW MARKLOGIC HELPED How MarkLogic helped English, Africans Data linkage Tracks Stations, Assets, Signal Train movements Data linkage Fast integration Variety of formats Easy data consolidation Exploration Analysis Data linkage Semantics Geo spatial Schema agnostic Search

24 Live Demo

25 Any Questions?

26 Thank you for your attention! EBCONT proconsult GmbH Millennium Tower Handelskai Vienna Austria WE ARE LOOKING FORWARD TO INTERESTING DISCUSSIONS