2021 was a year full of unexpected data integration challenges, but one thing that didn’t change was the continued growth of the importance and value of data. By watching our customers adapt and cope through the consistent application of technology, we’ve learned that the future can be quickly adjusted to if we have up-to-date and readily available data to make decisions. As we consider the data integration landscape and look forward into 2022, we see a set of trends (some new, some old) that data leaders will need to consider as they work to provide competitive business value to their organizations: - The Continued Importance of Spatial - Data Ops as a Practice - Rising Data Volumes Demand Data Quality - Ubiquitous Hardware Supporting Augmented Reality - Agile Enterprise Integration Effortlessly Connects Systems - Real-Time Data Stream Processing - Flexible, Hybrid Deployment Options - Cost effective ARM based processing In this webinar, join co-founders Don Murray and Dale Lutz as they offer insight and predictions on what’s to come in these areas. To follow, they’ll host a Q&A session where you can get feedback and advice on solutions to your data challenges.

1. 7 Emerging Data & Enterprise
Integration Trends in 2022

2. Meet the Presenters
Don Murray
Co-Founder
Dale Lutz
Co-Founder

3. What are your biggest
data challenges?
Chat storm…

4. Businesses that maximize
data value through
better decisions
win in the marketplace.

5. Data Integration is all about
transforming data into decisions.

6. .
25+ years
helping organizations maximize the value of data
10,000+ Organizations
trusting us worldwide
128 Countries
with FME customers
150+ Partners
supporting our customer network
Safe Software
Company Profile
www.safe.com

7. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of
the entire document. The Gartner document is available upon request from Safe Software.
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise
technology users to select only those vendors with the highest ratings or other designation. Gartner research publications
consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner
disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or
fitness for a particular purpose.
Safe Software
Recognized for second year in the
2021 Gartner Magic Quadrant
for Data Integration Tools.

8. FME®
Integration Platform
Connect. Transform. Automate.
FME Desktop FME Server FME Cloud
Build & Run Data Workflows Automate Data Workflows
(on-premises)
Automate Data Workflows
(cloud)
Get a free trial of FME Desktop and FME Server at safe.com

9. Data Integration Trends to Watch in 2022
1. Explosive Growth of Data
2. Growth of Spatial Data
3. Augmented Reality
4. Agile Enterprise Integration
5. Real-Time Data Streaming
6. Hybrid Solution Deployment
7. ARM for the Cloud and Mac OS

10. 1. Explosive Growth of Data
More data is collected than ever before. Processing, and distilling it to
make better decisions is both a challenge and an opportunity.

11. 1. Explosive Growth of Data
To meet rising demand,
organizations need to be
prepared to scale their data
processing resources.
According to the IDC:
By 2025, 175 trillion
gigabytes of new data will be
created around the world.

12. Meeting the challenge: Data Growth
Approach #1: Deliver a Faster and more memory efficient Engine.
Saving you time and making new things possible.

13. Bulk Processing: A faster way to process data
Save Time and Process Larger Data Volumes than ever
Bulk Processing: data processed in blocks for higher efficiency
Algorithmic Bulk Optimizations: massive performance improvements

14. Bulk Processing Sample Improvements
Scope Runtime
Filtering data into smaller groups
E.g. AttributeFilter, DuplicateFilter, or Tester
Up to 60% less time
Datasets containing string attributes Up to 25% less time
Processing that groups data (Group By) Up to 60% less time
Processing that uses a subset of attributes Up to 35% less time

15. Specific Bulk Data Improvements
Scope Runtime
FeatureWriter using dataset or feature type fanout Up to 40% less time
Datasets with few rows and many attributes Up to 99% less time
Processing that create bulk data when input data has
large geometry
E.g. Cloner or AttributeKeeper
Up to 99% less time

16. Example FME 2022.0 Performance
Scenario: Reading 29
million rows from CSV,
filtering by a column, and
calculating grouped median
statistics
5x faster vs FME 2021.2
Using 5% of the memory

17. Parallel Processing: The Power of many engines
Save Time and Process Even Larger Data Volumes!
Engage Multiple engines: divide and conquer large processing requirement
Pay For work that is done: cpu pricing enables you to pay for work done regardless of
how many engines you engage.

18. Meeting the challenge: Data Growth
Approach #2: Deliver no-code Parallel Processing Interface

19. Parallel Processing

20. CPU-Usage Pricing Perfect for
Parallel Processing
● CPU-Processing based pricing.
● Ideal for varied workloads, streaming,
and large processing workflows
● Called Dynamic Engines
CPU Usage Pricing
● Fixed FME Server processing power
● Ideal for customers with predictable
and consistent workloads
Standard Engines
Standard and dynamic engines can be used together

21. Benefits
● Save time by engaging many engines
● Process large datasets efficiently
● Do things that before were
impossible.

22. 2. Growth of Spatial Data
“Location” is critical to a whole new set of decisions supporting new
business efficiency workflows

23. 2. Spatial Data Growth Continues

24. More recognizing the importance of spatial data.
The Rise of Spatial Data
And many more....
Watch for the trend to continue with more vendors and technology
providers embracing spatial data.

25. Power of Data Type Support
However more value can be achieved from
data assets when they are combined in
different ways.
It is by combining and mixing data types that
organizations create new insights.
Each type of data has value and is collected to answer specific questions or measure
a certain conditions.
Comprehensive support for spatial is required for many decisions.

26. We continue to also expand the reach of FME!

27. 3. Augmented Reality
Experience your data in context to improve efficiency
and accuracy of infrastructure planning and maintenance.

28. 3. Augmented Reality
Facilities Management AR Examples
● Locate, view underground/surface assets
● Seeing indoor infrastructure inside walls
● Visualizing historic or planned buildings
and assets.
Blog: 5 Ways to View Your Data in AR
Augmented Reality needs location to be effective and requires seamless integration of
many different types of data for a rich experience!
Automated Reality demonstrates the power of many data types powering new
decision making and workforce efficiency workflows.

29. Mobile Sensors + Cloud Processing + AR = MAGIC
-> Drain basins
-> Road surface analysis
https://youtu.be/XVwK_nDBcHM
https://youtu.be/qU2AmYYPwXY

30. Is 2022 The Year of the AR Glasses?

31. 4. Agile Enterprise Integration
Deliver fast decisions with constantly changing data processing
requirements.

32. ● Saves your team time
● Increases productivity
● Increases efficiency
● Minimizes errors
● Standardized processes
● Better customer experience
● Increases scalability
Benefits of Data
Integration are many

33. Enterprise Integration Demands constantly changing
Solution must be agile to be able to handle any peak.

34. Automation
Individual Level
Eliminate lightweight manual tasks such as data validation, data entry, report building,
data sharing, simple email communication, notifications
Department Level
The shift from monolithic applications to razor focused applications continues. This
results in the need to synchronize information across applications and departments
Organizational Level
Ensure heterogeneous IT environments are connected with Enterprise Integration.

35. Types of Automation on FME Server
● Real-time event Automations: Connecting applications for more accurate, timely
and efficient processes
● User driven FME Server Apps: Information to decision makers when they want it.
● Real-time Data Stream processing: Understand what is happening now.
● Periodic scheduled tasks: Automatic reporting and scheduled data (ETL) movement
tasks.
3 of the 4 types of FME Server Automations flows are real-time!

36. CPU-Usage Pricing Perfect for
Agility
● CPU-Processing based pricing.
● Ideal for varied workloads, streaming,
and large processing workflows
● Called Dynamic Engines
CPU Usage Pricing

37. 5. Real-Time Data Streaming
Improve customer service and situational awareness with real-time
decision making

38. Real Time Streaming Data
Due to the proliferation of sensors and 5G, organizations need to analyze and manage
more real-time data than ever before
Examples:
● Web Data (ex. website visits, social media, applications)
● IoT Data (ex. sensors, meters, devices)
● Real-Time Events (ex. Fire alarm, heat sensor)
● Continuous streams (ex. moving assets, app log streams)
Organizations must work with all real-time data types to make fast, accurate decisions

39. 6. Hybrid Solution Deployment
Organizations need solutions that run both in the cloud and on-premises.

40. Evolution to the Cloud
Factors driving organizations to the cloud:
● Remote workers - COVID19 has accelerated the move to remote work
● Scalability & elasticity - Trend towards pay for what you use rather than capacity.
● Serverless services - From DBʼs to other services pay for use and level of service.
● Serverless compute - leverage open source container technology (i.e. Kubernetes)
● Enhanced security - Build on the secure platform of cloud vendors
Resource: Understanding
Cloud Agnostic Strategies
Cloud technology is evolving fast.
Select data management tools that are cloud agnostic.

41. Data Gravity and Growing Data
Applications and Services benefit
by being close to the data.
The closer they get
● Throughput goes Up
● Latency goes Down
As Data volumes increases so
Does Data Gravity.
What is Data Gravity?

42. As close to the data as possible!!!
Where is the Best Place for Processing?

43. Hybrid Deployment
On Premises
Data Gravity is real! Processing close to the data is best.

44. Can we have a slide here that shows a map with the regions
we support?
Reasons could be regulatory (not allowed to have data
outside your country)
Data Gravity - Better response delivers better experience
when processing is close to the data.
Current Regions for FME Cloud
More regions added upon customer requests!
Data Gravity is real. Processing close to the data is best.

45. Azure and Google Cloud
The FME Platform is built to be
cloud agnostic. Deploy it
anywhere you need to.
Cloud marketplace listings
support a one click deployment
of FME Server into the
customerʼs cloud account.

46. 7. ARM for the Cloud and Mac OS
Ability to embrace latest trends to bring more cost effectiveness.

47. ARM Processor:
Changes the Game
Game changing with unmatched performance
per watt becoming important!
Desktop: Cooler, faster, smaller, longer battery,
no fan
Data Center: Cooler, faster, smaller, lower cost
Processor technology changes over time.
Look to data management tools from vendors that embrace change.

48. AWS Graviton Instances
FME Platform will support Graviton
instances in FME 2022.0, continuing
leading the way in deployment
options.

49. Early Apple Silicon Results

50. Businesses that maximize
data value through
better decisions
win in the marketplace.

51. Data Integration is all about
transforming data into decisions.

52. Poll:
What trend do you see being the
most impactful to your business?

53. The Peak of Data Integration 2022 UC
August 24-26, 2022 Vancouver, Canada
Appy to present | Register now

54. Check out our upcoming
& on-demand webinars:
safe.com/webinars

55. Claim Your Community Badge
Get community badges for
watching webinars!
fme.ly/WebinarBadge Todayʼs Code: FMPWC

56. Thank You!
Connect with us for more FME
Please share
your feedback
with us through
the webinar
survey!
Please complete Customer Gartner Survey: http://fme.ly/dm-gartner