The document discusses the importance of real-time analytics and data visualization in various industries, highlighting the role of IoT and advanced analytics in transforming business operations. It outlines six requirements for effective IoT visualization, including streaming data visualization and predictive analytics, emphasizing the need for real-time insights and data preparation. Case studies illustrate how companies are adopting these technologies to reduce costs and improve efficiency.

1. ADVANCED ANALYTICS
FOR ANY DATA
AT REAL-TIME SPEED
Dan Potter
Chief Marketing Officer, Datawatch Corporation

2. How Many Sensors
Are In Your Pocket?

3. NASDAQ: DWCH
Pioneer in real-time visual data discovery and self-service data
preparation
Global operations and support
 US, UK, Germany, France, Australia, Singapore, Philippines
Extensive global customer base
 93 of the Fortune 100
 12 of the 15 largest financial institutions
Embedded and resold by leading vendors
About Datawatch

4. IoT and Industrial Analytics
50 billion devices will be interconnected by 2020
- Cisco
By 2017, over 50% of analytics implementations will make use of
event data streams generated from instrumented machines,
applications and/or individuals
- Gartner
Real-time visualization leads to more opportunities, greater
output, and lower costs
- Aberdeen Group
IoT companies attracted more than $1 billion in venture capital
- Forbes

5. What is Industrial Big Data?

6. IoT Platform Requirements
Stream
Processing
Visual Data
Discovery
Real-Time
Transport
Sensor
Data
OT
Data
IT
Data

7. Visualization for IoT
Data
Access
Visual
Discovery
Monitor
and Alerts
Data
Preparation Predictive
Analytics
Take
Action

8. 6 Requirements for IoT Visualization
Data Discovery
Streaming Data Visualization
Time Series Data
Predictive & Advanced Analytics
Data Preparation
Real-time Geospatial & Location

9. #1 Data Discovery, not just Dashboards
• Easy for users to author,
customize and share
• Interactive exploration &
visually filter results
• Quickly identify
anomalies and outliers
with large or in-motion
datasets
• Rich palette of
visualizations for static
and time series data

10. #2 Streaming Data Visualization
Database Distributed or
Hybrid Database
In-Memory
Database
Streaming Analytics
Faster Speed, Faster Insights

11. Data at Rest
Limitations of Traditional BI
Database Distributed or
Hybrid Database
In-Memory
Database
Streaming Analytics

12. Data at Rest
Streaming Data Discovery
Database Distributed or
Hybrid Database
In-Memory
Database
Streaming Analytics

13. Streaming Data Discovery
Database Distributed or
Hybrid Database
In-Memory
Database
Streaming Data
Alert! Steam turbine stress
level over threshold
How does this compare to
intra-day? What is mean
time to failure?
What is likely to occur?
Act! Schedule shut down

14. Streaming Data Visualization
• Connect directly to data in motion
• Hosted IoT platforms
• Complex Event Processing & MQ
• Data model optimized for both caching and persistence
• High density visuals with rendering in milliseconds
Monitor Analyze Take Action

15. #3 Time Series Data
• Traditional BI only looks at buckets of
time
• Day, week, month, year
• Sensor data is a continuous and has
different requirements
• Second, millisecond, nanosecond
• Time windows
• Time slices
• Playback
• Complete situational awareness
• Now (streaming)
• Intra-day
• Historic

16. #4 Predictive & Advanced Analytics
• Enrich streaming OT data
with “what is likely to occur”
• Predictive models based on
historic data patterns
• Many use cases in IoT (e.g.
predictive maintenance,
smart logistics, clinical
pattern detection etc.)
• Leverage commercial and
open source solutions

17. We Want to Predict the Future for
Equipment

18. Modeled and
transformed
for analysis
#5 Data Preparation
• Sensor and machine data often in multi-structured format
• Need to transform, enrich and prepare data
• Almost no metadata
• For example, wave form visualization from JSON arrays
stored in MongoDB and streaming
Log Files
HTML,
XML JSON
PDFs

19. #6 Real-Time Geospatial & Location
• Real-time (stream) plotting
• Street-level geo maps or
custom SVG files
• Time-series playback
HealthcareRetail Logistics
Utilities

20. 6 Requirements for IoT Visualization
Visual Data Discovery
Streaming Data Visualization
Time Series Data
Predictive & Advanced Analytics
Data Preparation
Real-time Geospatial & Location
New
Analytic
Approach
Required

21. The Next Wave of Business
Transformation
Source: Industrial Analytics: The Next Wave of Business Transformation
Gartner, March 2014

22. ROI for Real-Time Data Visualization
Growth in New Pipeline
Increase in Cash Generated
Greater Operational Cost Reduction
“Real-Time Data Visualization” October 2013

23. Customer Use Case
• Fortune 500 oil & gas exploration and production company
• Moving to real-time streaming visualization
• From 24 hour latency moving data overnight from OSIsoft Pi to Oracle Warehouse
feeding dashboards
• To real-time, streaming data discovery connecting directly to OSIsoft Pi server
• Initial goal is to reduce steam cost by 3-5% ($M) in year 1
Pi Server

24. Smart Meter Dashboard
Streaming data from electric smart meters

26. Hospital Emergency Ward – Bird’s Eye View
Streaming data from patient monitoring system

27. Workbook