Learn more about it here: https://www.youtube.com/watch?v=6mSg6ij0Fak Albert presents how effectively gather functional requirements for sensor data analytics, which aspects are the most important for designing IoT data platform and which steps needs to be taken to implement such solution to gain great return on investment. Watch our webinar about profit from IoT: https://www.youtube.com/watch?v=6mSg6ij0Fak&t=3s If you would like to read something more about IoT, please do not hesitate to download our white paper "Data Analytics for Industrial Internet of Things": https://getindata.com/blog/white-paper-big-data-analytics-industrial-internet-things/ Speaker: Albert Lewandowski Linkedin: https://www.linkedin.com/in/albert-lewandowski/ ___ Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets. Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries. https://getindata.com​

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

30. 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

46. https://getindata.com/blog/success-story-breastfeeding-s
upported-with-modern-iot-app-features-bigquery-cloud
Mamava

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

50. Whitepaper
https://getindata.com/blog/white-paper-big-data-analytics
-industrial-internet-things

52. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Q&A

53. Thank you
for your attention!