This document is offered compliments of
BSP Media Group. www.bspmediagroup.com
All rights reserved.
Real-Time Analytics
Process Automation

Nico Coetzee
ncoetzee1@fnb.co.za

First National Bank – a division of FirstRand Ba...
Big Data
• Volume
• Amount of data

• Velocity
• speed of data in and out

• Variety
• Range of data types and sources
Volume
• Examples:
• User profile database
• Inventory

• Real Time Analytics Scenarios:
• Measure changes over time
• Ass...
Velocity
• Examples:
• POS Transactions (think big national retailers)
• Logs (firewall logs)

• Real Time Analytics Scena...
Variety
• Examples:
• End-to-end transaction flows through Web
logs, Application server logs and database logs

• Real Tim...
The “Missing” V’s
• Viability
• The secret is uncovering the latent, hidden
relationships among these variables.

• Value
...
Technologies to Consider
• MongoDB
• NoSQL DB
• Distributed operations (Grid FS)
• Built-in Map-Reduce engine

• Syslog-ng...
The Future
• DevOps and Agile methodologies can
benefit from the inputs from real time Big
Data analytics
• Identified (po...
Thank You
Real- Time Analytics – Process Automation
Real- Time Analytics – Process Automation
Real- Time Analytics – Process Automation
Real- Time Analytics – Process Automation
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Real- Time Analytics – Process Automation

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Real- Time Analytics – Process Automation

  1. 1. This document is offered compliments of BSP Media Group. www.bspmediagroup.com All rights reserved.
  2. 2. Real-Time Analytics Process Automation Nico Coetzee ncoetzee1@fnb.co.za First National Bank – a division of FirstRand Bank Limited. An Authorised Financial Services and Credit Provider (NCRCP20).
  3. 3. Big Data • Volume • Amount of data • Velocity • speed of data in and out • Variety • Range of data types and sources
  4. 4. Volume • Examples: • User profile database • Inventory • Real Time Analytics Scenarios: • Measure changes over time • Assist ERP systems with automation (order stock) • Stock load balancing (automatically redistribute stock from one area to another)
  5. 5. Velocity • Examples: • POS Transactions (think big national retailers) • Logs (firewall logs) • Real Time Analytics Scenarios • Sudden unexpected patterns (a region experiences an outage) • Attacks and other anomalies that can be picked up from logs
  6. 6. Variety • Examples: • End-to-end transaction flows through Web logs, Application server logs and database logs • Real Time Analytics Scenarios: • Continues monitor response times (very handy for Cloud type solution where decisions to start more VM’s may be required) • Context required for making intelligent decisions, for example in anti-fraud systems
  7. 7. The “Missing” V’s • Viability • The secret is uncovering the latent, hidden relationships among these variables. • Value • Remember: Correlation does not mean causation • Realistic scenarios: Was your marketing campaign successful?
  8. 8. Technologies to Consider • MongoDB • NoSQL DB • Distributed operations (Grid FS) • Built-in Map-Reduce engine • Syslog-ng • Real time decisions on log events • Granular control over log routing • Rules based on regular expressions
  9. 9. The Future • DevOps and Agile methodologies can benefit from the inputs from real time Big Data analytics • Identified (potential) defects should naturally flow back into the backlog. • Infrastructure and resource management
  10. 10. Thank You

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