IoT Enabled TechnologiesDelivering Actionable Insights for the Telecom Industry

Joe Pusztai

VP, Solution Marketing

Datawatch

Syed HodaChief Marketing Officer

ParStream

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Strong IoT momentum with CEO’s & CIO’s

Predictions 2015IoT software platforms will become the

rage in 2015 and drive IoT Adoption

Top 10 Strategic Technology Trends for 2015

1. Computing Everywhere

2. Internet of Things

3. 3-D Printing

4. Advance, Pervasive Analytics

5. Context-Rich Systems

6. Smart Machines

7. Cloud Computing

8. Software Defined Infrastructure

9. Web-scale IT

10. Risk-Based Security

2015 Tech Predictions

1. Digital transformation

2. Internet of Things

3. Convergence of big data with consumer data

4. Hybrid cloud

5. Collaboration

6. Predictive analytics will lead big data

7. Mobile wearable technology

8. A Platform and orchestration is needed

9. Networked Economy

10. The end of apps

Better IoT data collection and analysis would deliver more value

• 70% say they would make better, more meaningful decisions with improved data

• 86% would increase the ROI of their IoT investment

IoT not delivering full potential because of data challenges

• 86% of stakeholders in business roles say data is important to their IoT project

• Only 8% are fully capturing and analyzing IoT data in a timely fashion

• 94% face challenges collecting and analyzing IoT data

IoT projects vary widely – but all have challenges

• 53% are using IoT projects to optimize existing businesses and 47% as a strategic

business investment

• 96% have faced challenges with their IoT projects (#1 process, #2 users, #3 data)

Global IoT Survey: Key Findings

What does IoT really mean …

Intelligent connections that capture real-time events which enable

companies to transform their Sense and Respond capabilities driving

speed, efficiency, and quality.

The key to generating value from IoT data: Actionable Insights

Data

REAL-TIME DATA INGESTION + IMMEDIATE QUERIES

= ACTIONABLE/TIMELY INSIGHTS

Action

Devices

Devices

Devices

Rules or On-

demand InsightsA

ggre

gation

Time = Money! There is business value in immediately analyzing real-time data in IoT

Imagine a world…

Where IoT analytics enable an energy company to…

30TBAnalyze Data

in Real-time

15%Increase

Efficiency

$18K/hr; $158M/yrGenerate Operational/

Economic Benefits

(20,000 Wind Turbines; 10 GW Capacity; .3 Capacity Factor; $40/MW-hour)

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IoT analytics has a set of distinct requirements

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Big DataData is growing faster and bigger

because of more sensors

10B+ rows

5TB+

Fast DataData streamed from sensors

requires fast ingestion

1M+ rows

per sec

Edge AnalyticsIoT data is mostly generated

at the ‘Edges’ of the network

100+

Locations

Real-Time InsightsUse cases require near

Real Time Analytics

<1 sec query

response

time

Existing products don’t fulfill IoT requirements

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Product

Requirements

Columnar

Databases

Vertica,

Redshift

Row-based

Databases

Oracle,

Informix...

Value

Stores

Cassandra,

MongoDB

Hadoop

Batch

Cloudera,

Hortonworks

Hadoop

Streaming

Spark / Shark

Storm

BIG DATACapacity –

FAST DATA Import – –

EDGEAnalytics Capability – – – – –

REAL TIME Insights – – – – –

INTEGRATEDPlatform – – –

IoT DATAStorage Structure – – –

See details in backup

ParStream and Datawatch introduce the first analytics platform built for IoT

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IoT Data Collection Platforms Enterprise Data Sources

ParStream DB

Geo-

Distributed

Analytics

Alerts +

Action

Time

Series

Advanced

Analytics

Choose your database based on your use-case

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< 1..10 ms

1 min

1 hr

10..100 ms

1 sec

10 min

4 hrs

Resp

on

se T

Ime

Big Data

Massively parallel (MPP)

Real-Time

Hadoop / Cassandra / ImpalaOLTP

Reporting

In-Memory DB

Gigabyte Terabyte Petabyte

OLAP

Batch-Analytics

Real-Time IoT

Analytics

Stream-Analytics

Operations

Analytics

Complex Event

Processing

High

Low

ParStream is uniquely positioned for Real-time Analytics in IoT

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REAL-TIME

IMPORT

REAL-TIME

QUERYING

FLEXIBLE

ANALYTICS

Small Form Factor / Low TCO

Bil

lio

ns

of

Re

co

rds

Thousands of Columns

ParStream has the fastest query response times

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Environment: Single EC2 XL node with 15 GB RAM, 2 TB disk on Amazon AWS.

OTP data set with 150 Million records. Query set based on customer use-cases.

RedShift

1 second

10seconds

22seconds

31seconds

38seconds

98seconds

Edge analytics delivers real-time insights by minimizing network traffic

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20 Billion Rows

40 records found

ParStream

ParStream Geo-Distributed Server

3

rows

14

rows

5

rows

12

rows

6

rows

ParStream ParStream ParStream ParStream

40 Rows

ApplicationApplication

Centralized

storage

40 records found

4B

rows

4B

rows

4B

rows

4B

rows

4B

rows

Traditional Analytics Edge Analytics

ParStream introduces EdgeAnalyticsBox• Specifically designed to enable edge analytics

• Ruggedized for use in real-world edge analytics applications

such as oil/drilling sites, cell phone towers, wind farms, etc.

Industry-leading Product Recognition

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ParStream is the most

reliable System in our Data

Center

CTO, etracker

"ParStream’s ability to

analyze terabytes of data

with sub-second response

time helps us generate

significant value."

President, Envision Energy

ParStream enabled us to

scale internationally - TCO

is much lower than with

Hadoop

VP Eng, Searchmetrics

#1

Big Data

Startup

Cisco Entrepreneurs in Residence 2014 IoT Excellence Award

About Datawatch

NASDAQ: DWCH

Pioneer in real-time visual data discovery

and data preparation

Global operations and support

US, UK, Germany, France, Australia,

Singapore, Philippines

Extensive global customer base

99 of the Fortune 100

12 of the 15 largest financial institutions

Resold and embedded by leading vendors

Visual Data Discovery enabling meaningful and timely decisions for IoTanalytics.

• Single, integrated platform

• Modular approach

– Start on the Desktop and add

Server capabilities when

ready

– Deploy any or all capabilities

• Complements with your

existing investments

– Deploy with other BI tools,

ETL and data warehouse

technologies

Visual Analytics Platform

Datawatch Architecture

AutomationService

ContentRepository

VisualizationEngine

In MemoryCache

Prepare & Design

Top IoT Challenge in Telecom

From 2.4 billion in 2012 to an

estimated 18 billion by 2022

(22% CAGR)

Largely driven by connected

consumer electronics

New services such as

streaming media & all-you-can-

eat LTE are putting huge strains

on network performance

Real-time monitoring of

bottlenecks and demand spikes

are essential to avoid outages

and QoS degradation…

M2M Traffic Explosion

Top Operational Requirements in Telecom

• Real-time performance monitoring to:

– Ensure maximum uptime

– Anticipate and provision for peak demand

– Provide improved customer service

– Increase customer loyalty

– Schedule preventative maintenance

• Real-time usage monitoring & alerting

– Subscriber bill shock remains a chronic problem

– Proactive alerting of roaming, excess data charges, connected devices

are becoming vital to customer service

• Mobile Device Management

– High availability & security of mobile devices and applications are

mission-critical to an increasing number of businesses

Technology Requirements for IoT Analytics

Visual Data Discovery

Streaming Data Visualization

Time Series Data + Multiple Time Horizons

Predictive & Advanced Analytics

Complex File Formats

Real-time Geospatial & Location

1/ Visual Data Discovery

• 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

Data at Rest

2/ Streaming Data Visualization

Database Distributed or

Hybrid Database

In-Memory

Database

Streaming Analytics

3/ Time Series + Time Horizons

• Traditional BI only looks at coarse

buckets of time:

– Year > Quarter > Month > Week > Day

• Events are continuous and have varying

analysis requirements:

– Second, millisecond, microsecond

– Time windows

– Time slices

– Playback

• Visibility of all time horizons -> complete

situational awareness:

– Now (streaming)

– Intra-day

– Historic

4/ Predictive & Advanced Analytics

• Text Analytics– Entity Extraction

– Sentiment Analysis

• Predictive Analytics– Regression

– Clustering

– Machine learning

• Many IoT Use Cases– Predictive maintenance

– Subscriber churn

– Smart logistics

– Clinical pattern detection

Modeled and

transformed

for analysis

5/ Complex Data & File Formats

• Real-world data is multi-structured

• Often no metadata – must be induced from the data

• Blurred line between “Data in Motion” & “Data at Rest” (e.g. log

file ingestion at one-second intervals)

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Log Files

HTML, XML JSON

PDFs

6/ Real-Time Geospatial & Location

• Real-time (streamed) plotting

• Geo-coded street-level maps

• Customized SVG files

• Time-series playback

HealthcareRetail

Logistics

Utilities

Telecom IoT Solution Demonstrations

The Next Wave of Business Transformation

Source: Industrial Analytics: The Next Wave of Business Transformation

Gartner, March 2014

Visualization: Goals -> Design

If Goal Is… Visual Design Includes… Examples

Profitability

High-density displays, multiple data

sources, sophisticated models,

streaming data, detection of “profit-

making events”

Trading desk applications,

marketing automation

ControlDomain-specific data sources, limited

analysis features, positive feedback

loops (alerts and actions)

Energy grid monitoring,

digital oilfield, industrial and

financial process control

applications,

Persuasion

Audience-specific, visually polished

presentation: attractive colors, “story

telling”, infographics

Executive / KPI dashboards,

customer-facing marketing

applications

Knowledge

As many data sources as is required to

gain insight, highly-granular data,

ultimate analysis control (alt.

hierarchies, filters, time-series

playback), statistical discovery

Customer churn analysis,

sentiment analysis, product

traceability, strategy planning

applications

A Blueprint for Your Integrated IoT Analytics Platform

RulePoint

CEP

real-time

analytics

Visual & search

based data

discoverySensor Data

Stream

Real-time

actions

Real-time/Historical

reporting

Discover &

Deploy

Derive

Connectivity to “Things” (sensors, actuators)

IoT PlatformDevice-level protocols,

transport, security

Real-time

alerts

DatawatchVisual

Analytics

ParstreamAnalytical Database

Success Factors for your IoT Program

Find OT + IT convergence opportunities with dollarized business value (e.g. true per-subscriber profitability)

Leverage new generation of low cost sensors to create new data sources and deliver holistic system-wide view

Define “build or buy” criteria for every element of your IoT blueprint:

Purpose-built vs home-grown device & transport platforms

Commercial vs open-source for databases, event processing, predictive, visualization

Cloud vs on-prem vs hybrid deployment

Do not treat IoT initiatives as “IT projects”:

OT factors much larger than IT

Flexibility and rapid insights are more important than transactional integrity

Need cross-functional buy-in from non-traditional stakeholders

Sales, Marketing, Operations, Product Development

New mix of skills e.g. an individual “data scientist” rarely has the entire breadth of skills and knowledge

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Next Steps

www.parstream.com

Download the IoT Industry Survey at:http://sites.parstream.com/parstream-iot-survey-whitepaper

• Get in touch www.datawatch.com/contact-us/

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• Explore: www.datawatch.com/explore/

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