How to maximize profit from IoT by using data platform - Albert Lewandowski, GetInData
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The document discusses how to maximize profit from the Internet of Things (IoT) through modern data platforms, emphasizing the importance of data processing, security, and analytics. It outlines various IoT applications across industries, highlights steps to implement IoT solutions, and provides guidance on building flexible data infrastructures. The text also stresses the significance of human skills in managing these technologies effectively.
How to maximize profit from IoT by using data platform - Albert Lewandowski, GetInData
- 1. How to maximize profit from Internet of Things using modern Data Platform? Author: Albert Lewandowski
- 2. • Big Data DevOps Engineer in Getindata • Member of the IoT working group in the Ministry of Digital Affairs • Consultant for startups • Focused on Industry 4.0, Smart City and Big Data sectors Who am I?
- 3. Ever-growing network of smart, connected devices, objects and appliances. - Gathering and transferring data - Access to to the internet What is Internet of Things?
- 4. - temperature and humidity sensors, - pressure sensors, - proximity sensors, - smoke sensors, - level sensors, What is Internet of Things? - accelerometers, - gyroscopes, - gas sensors, - infrared sensors, - optical sensors, - image sensors (like CCTV)
- 5. - Digital signage - In-store offering & promotions - Supply chain - Smart ordering & payment - Vending machines Retail
- 6. - Adherence & support - Clinical - Virtual care - Wellness & prevention Healthcare
- 7. - Health and life insurance - Home insurance - Industrial insurance - Vehicle insurance - Cross Insurance
- 8. - Assisted & autonomous driving - Fleet management - In-vehicle infotainment - Shared mobility - Smart navigation Connected cars
- 9. - Construction - Education - Energy - Environmental - Roads, traffic & transport - Social & Security Smart Cities & Energy
- 10. - Agriculture - Mining - Oils & gas Natural resources
- 11. - Connected field - Digital factory - Product design & engineering - Smart maintenance Connected Industry
- 12. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Data-based company
- 13. 1. Do you process data? 2. What kind of services do you use? 3. Do they support additional data sources? 4. Do you take advantage of being data-based company? 5. What is your data strategy? 6. What about security? 7. How much data do you already have? Questions
- 14. © Copyright. All rights reserved. Not to be reproduced without prior written consent. First steps with IoT
- 15. - Based on the network connection - Wireless - Wired - Based on the data processing - Edge - Central - Based on the sensor types Types of IoT
- 17. - Multiple data sources - Heavy-loading data processing if we want to process all information (especially video) - Network limitations Data analysis based on IoT
- 18. - How can we process the data on the edge? - How much data should we transfer? - Big Data solutions for your needs Data enrichment
- 19. © Copyright. All rights reserved. Not to be reproduced without prior written consent. IoT Data Analytics In Your Company
- 20. 1. Define problems. 2. Analyze your current IT stack and used solutions. 3. Prepare plan for next 6-8 weeks to create PoC. How to start?
- 21. - Which processes can be automated? - What are the targets of our project? - What do we plan to do in the future? Understanding problem
- 22. - Which structure of IoT devices is the most suitable for us? - How do we need to collect information? Do we need to send them to the central platform? Which type of IoT?
- 23. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Let’s build Data Platform
- 24. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Perception Business logic CI/CD Idempotency Reprocessing Explainability Monitoring Testing Serving Infrastructure Data Ingestion Security
- 25. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Reality Business logic CI/CD Idempotency Reprocessing Explainability Monitoring Testing Serving Infrastructure Data Ingestion Security
- 26. - Network - Security - Performance Which type of IoT?
- 27. - Multiregional setup - Private vs. public cloud - Backup and disaster recovery High Availability
- 28. - Audit features - Permissions management - Encrypt traffic between IoT devices - Update software and manage devices from one place Security
- 29. - Storage - Data ingestion - Data processing - ML / AI services - BI tools - Data visualisation - Compute resources - Managed or non-managed services Big Data Services
- 31. - Public cloud or own infrastructure? - Managed or non-managed services - How to store data? - Avoid vendor-lock - is it important? IT infrastructure
- 33. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Great services for IoT
- 34. - Start with simple pipelines. - Start with the simplest and most important use case for the company - Create flexible data infrastructure to add new components easily Data pipelines
- 35. Depends on: - amount of data - required time to deliver results - costs and complexity Central or Edge processing
- 36. Streaming or Batch Streaming Batch Process data continuously Process data in batch We process piece-by-piece Once data is collected, it’s sent for processing Fast results and react to defined triggers Great for processing large amount of data
- 37. - Do you need ML/AI? - What business value can it add to the project? - Edge AI Machine Learning
- 38. Observability
- 39. - Do we have in-house skills? - How big team do we need? - How to manage the project? Human skills
- 40. SRE & DevOps If a human operator needs to touch your system during normal operations, you have a bug. The definition of normal changes as your systems grow. Carla Geisser, Google SRE
- 41. SRE & DevOps If you think of DevOps like an interface in a programming language, class SRE implements DevOps.
- 42. SLI, SLA & SLO • SLA - Service Level Agreements • SLI - Service Level Indicators • SLO - Service Level Objectives
- 43. Measuring Service Risk Time-based availability is traditionally calculated based on the proportion of system uptime. Aggregate availability shows how this yield-based metric is calculated over a rolling window (i.e., proportion of successful requests over a one-day window).
- 44. CICD pipelines Besides black art, there is only automation and mechanization. Federico García Lorca (1898–1936), Spanish poet and playwright Source: AWS
- 45. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Stories from life
- 47. - Public-cloud based platform - Detect failures from devices in factories - Predictive maintenance - Real-time data streaming for analyzing information Industry 4.0, startup
- 48. - Private-cloud based platform - Real-time data streaming for analyzing information - Aggregating and analyzing data sent from edge devices Telecommunication, IoT data
- 49. - Public cloud-based startup - Security of the employees in the construction sites - Edge data processing Industry 4.0, startup
- 52. © Copyright. All rights reserved. Not to be reproduced without prior written consent. Q&A
- 53. Thank you for your attention!