IoT Enabled Technologies Delivering Actionable Insights for the Telecom Industry Joe Pusztai VP, Solution Marketing Datawatch Syed Hoda Chief Marketing Officer ParStream
Strong IoT momentum with CEO s & CIO s 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 Predictions 2015 IoT 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 2
Global IoT Survey: Key Findings 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) 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 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
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.
Aggregation The key to generating value from IoT data: Actionable Insights Devices Devices Data Rules or Ondemand Insights Action Devices REAL-TIME DATA INGESTION + IMMEDIATE QUERIES = ACTIONABLE/TIMELY INSIGHTS
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 30TB Analyze Data in Real-time 15% Increase Efficiency $18K/hr; $158M/yr Generate Operational/ Economic Benefits 7 (20,000 Wind Turbines; 10 GW Capacity;.3 Capacity Factor; $40/MW-hour)
IoT analytics has a set of distinct requirements Big Data Data is growing faster and bigger because of more sensors 10B+ rows 5TB+ Fast Data Data streamed from sensors requires fast ingestion 1M+ rows per sec Edge Analytics IoT data is mostly generated at the Edges of the network 100+ Locations Real-Time Insights Use cases require near Real Time Analytics <1 sec query response time 8
Existing products don t fulfill IoT requirements Product Columnar Databases Row-based Databases Value Stores Hadoop Batch Hadoop Streaming Requirements Vertica, Redshift Oracle, Informix... Cassandra, MongoDB Cloudera, Hortonworks Spark / Shark Storm BIG DATA Capacity FAST DATA Import EDGE Analytics Capability REAL TIME Insights INTEGRATED Platform IoT DATA Storage Structure See details in backup 9
ParStream and Datawatch introduce the first analytics platform built for IoT Geo- Distributed Analytics Alerts + Action Time Series Advanced Analytics ParStream DB IoT Data Collection Platforms Enterprise Data Sources 10
Response TIme Choose your database based on your use-case High Stream-Analytics Complex Event Processing Real-Time IoT Analytics < 1..10 ms 10..100 ms In-Memory DB Massively parallel (MPP) Real-Time 1 sec Operations Analytics OLAP Batch-Analytics 1 min 10 min OLTP Reporting Hadoop / Cassandra / Impala 1 hr Low 4 hrs Gigabyte Terabyte Petabyte Big Data 11
ParStream is uniquely positioned for Real-time Analytics in IoT Billions of Records REAL-TIME IMPORT REAL-TIME QUERYING FLEXIBLE ANALYTICS Small Form Factor / Low TCO Thousands of Columns 12
ParStream has the fastest query response times RedShift 1 second 10 seconds 22 seconds 31 seconds 38 seconds 98 seconds 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. 13
Edge analytics delivers real-time insights by minimizing network traffic Traditional Analytics Edge Analytics Application Application 40 records found 40 records found Centralized storage 20 Billion Rows ParStream Geo-Distributed Server 40 Rows 4B rows 4B rows 4B rows 4B rows 4B rows ParStream 3 rows 14 rows 5 rows 12 rows ParStream ParStream ParStream ParStream 6 rows 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. 14
Industry-leading Product Recognition Cisco Entrepreneurs in Residence 2014 IoT Excellence Award #1 Big Data Startup ParStream is the most reliable System in our Data Center CTO, etracker ParStream enabled us to scale internationally - TCO is much lower than with Hadoop VP Eng, Searchmetrics "ParStream s ability to analyze terabytes of data with sub-second response time helps us generate significant value." President, Envision Energy 15
About Datawatch Visual Data Discovery enabling meaningful and timely decisions for IoT analytics. 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 Analytics Platform 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
Datawatch Architecture Automation Service Content Repository Visualization Engine In Memory Cache Prepare & Design
Top IoT Challenge in Telecom M2M Traffic Explosion 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-caneat LTE are putting huge strains on network performance Real-time monitoring of bottlenecks and demand spikes are essential to avoid outages and QoS degradation
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
2/ Streaming Data Visualization Data at Rest 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
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) Log Files HTML, XML JSON PDFs Modeled and transformed for analysis 26
6/ Real-Time Geospatial & Location Real-time (streamed) plotting Geo-coded street-level maps Customized SVG files Time-series playback Utilities Retail Healthcare Logistics
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 Control Persuasion Knowledge High-density displays, multiple data sources, sophisticated models, streaming data, detection of profitmaking events Domain-specific data sources, limited analysis features, positive feedback loops (alerts and actions) Audience-specific, visually polished presentation: attractive colors, story telling, infographics As many data sources as is required to gain insight, highly-granular data, ultimate analysis control (alt. hierarchies, filters, time-series playback), statistical discovery Trading desk applications, marketing automation Energy grid monitoring, digital oilfield, industrial and financial process control applications, Executive / KPI dashboards, customer-facing marketing applications Customer churn analysis, sentiment analysis, product traceability, strategy planning applications
A Blueprint for Your Integrated IoT Analytics Platform Real-time actions Connectivity to Things (sensors, actuators) RulePoint CEP real-time analytics Real-time alerts Real-time/Historical reporting Derive Sensor Data Stream Discover & Deploy Visual & search based data discovery IoT Platform Device-level protocols, transport, security Parstream Analytical Database Datawatch Visual Analytics
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 32
Next Steps Get in touch www.datawatch.com/contact-us/ Discover more about Datawatch solutions: Explore: www.datawatch.com/explore/ Evaluate: www.datawatch.com/free-trial/ www.parstream.com Download the IoT Industry Survey at: http://sites.parstream.com/parstream-iot-survey-whitepaper
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