Contenu connexe Similaire à (BDT207) Use Streaming Analytics to Exploit Perishable Insights | AWS re:Invent 2014 (20) Plus de Amazon Web Services (20) (BDT207) Use Streaming Analytics to Exploit Perishable Insights | AWS re:Invent 20142. © 2014 Forrester Research, Inc. Reproduction Prohibited
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7%
16%
15%
18%
20%
24%
5%
12%
18%
17%
16%
33%
Social related projects
Mobile related projects
Cloud related projects
Systems of engagementapplications
Systems of record applications
Data related projects
2nd Priority
Top Priority
Source:ForrsightsSoftware Survey, Q4 2013, Base: 2,074 IT executives and technology decision-makers
Please rank the following technologies according to their importance and investment within your firm?
Executives and technology decision-makers are remembering the power of data. 7. Momentum is strongest for streamingand predictive analytics, but underadopted.
10%
13%
16%
18%
21%
21%
24%
29%
33%
37%
49%
50%
56%
58%
81%
15%
21%
20%
20%
27%
32%
19%
33%
42%
35%
50%
54%
59%
57%
77%
Non Modeled Data Exploration And…
Streaming Analytics
Advanced Visualization
Text Analytics
Metadata Generated Analytics
Predictive Analytics
Search/Interactive Discovery
Location Analytics
Process Analytics
Olap
Embedded Analytics
Performance analytics
Web Analytics
Dashboard
Reporting
2014
2012
“What is your firm's/business unit's current use of the following technologies?”
Source: Forrester Research
+62%
+52% 8. © 2013 Forrester Research, Inc. Reproduction Prohibited
8
What are the main business and technical requirements or inadequacies of earlier-generation business intelligence technologies that lead you to consider new BI techniques and technologies?
Base: 452 North American technology decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
Base: 249 North American business decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
2%
16%
20%
28%
29%
31%
32%
32%
34%
35%
45%
2%
12%
14%
26%
23%
35%
28%
31%
27%
33%
44%
Other (please specify)
Earlier-generation technology is too expensive
The velocity of data is too high for earlier technologies
The number of data formats that we must be able to…
Analysis requirements change too fast to keep up with
The performance of certain analysis is not sufficient
We don't know what our entire data universe contains,…
We want to access data that was not accessible for us…
Data changes or becomes available much faster than…
Data volumes have grown beyond what we can cost-…
We want deeper insights through advanced analytics
Business decision makers
Technology decision makers
Most want deeper insights through advancedanalytics but familar challenges persist. 9. © 2014 Forrester Research, Inc. Reproduction Prohibited
9
What percentage of enterprise data do firms use for analytics?
A.12%
B.34%
C.53%
D.76%
Enterprise
Data
Quiz 10. © 2014 Forrester Research, Inc. Reproduction Prohibited
10
What percentage of enterprise data do firms use for analytics?
A.12%
B.34%
C.53%
D.76%
Enterprise
Data
Quiz
Source: Forrester Research 13. Predictive analytics means faster decisions
10%
13%
16%
18%
21%
21%
24%
29%
33%
37%
49%
50%
56%
58%
81%
15%
21%
20%
20%
27%
32%
19%
33%
42%
35%
50%
54%
59%
57%
77%
Non Modeled Data Exploration And…
Streaming Analytics
Advanced Visualization
Text Analytics
Metadata Generated Analytics
Predictive Analytics
Search/Interactive Discovery
Location Analytics
Process Analytics
Olap
Embedded Analytics
Performance analytics
Web Analytics
Dashboard
Reporting
2014
2012
“What is your firm's/business unit's current use of the following technologies?”
Source: Forrester Research
+52% 14. © 2014 Forrester Research, Inc. Reproduction Prohibited
14
›Predictive models are about probabilities, not absolutes
•E.g. 78% chance you will like Breaking Bad
›Predictive models may not exist for every question
•E.g. Economists, elections, etc…
Predictive models can be very powerful and profitable, but understand that:
But, when they work they give your firm an “unfair” advantage. 15. © 2014 Forrester Research, Inc. Reproduction Prohibited
15
Data scientists use a combination of statistical and machine learning algorithms to find patterns and predictive models. 16. © 2014 Forrester Research, Inc. Reproduction Prohibited
16
Data science is very different from traditional analytics
Traditional Analytics
Predictive Analytics
•Choose a business outcome to improve
•Discuss and decide what data will be relevant
•Develop a data model
•Design reports and dashboards
•Choose business outcome to improve
•Assemble all possible data
•Run algorithms to find relevant data & predictive model
•Use the predictive model 17. How can Spotify use accelerometer data generated by customers while they listen?
Activity 20. © 2014 Forrester Research, Inc. Reproduction Prohibited
20
30%
7%
12%
21%
30%
9%
8%
14%
35%
34%
The term “big data” is very confusing; not sure what it means
It’s a bunch of hype with little substance and few new ideas
It’s about new technologies that allow us to handle more data
It’s an extension of existing analytics and BI practices suited for data that is larger or faster than we are used to
It’s a whole new way of thinking about the value in data that requires new analytics and leverages some new technologies
Business Decision Makers
Technology Decision Makers
Base: 452 North American technology decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
Base: 249 North American business decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
Most technology decision makers get it; 30% of business decision makers are confused. 23. Gather all your data to breakdown silos and prepare it for deeper analysis.
Data 28. . . . it’s also about raging torrents of data 29. © 2014 Forrester Research, Inc. Reproduction Prohibited
29
›Ingested and stored in a data warehouse
›Multiple sources of data
›Analytics run weekly, daily, or hourly
›Insights used to modify future actions
Analyzing data lakes versus streams
Streams
Lakes
›Does collect data in realtime
›Multiple sources of data
›Immediately fed to streaming application
›Analytics run continuously, second and subsecondresponses
›Insights used to proactively adjust immediateand future actions 32. Streaming analytics means real-time, actionable insights
10%
13%
16%
18%
21%
21%
24%
29%
33%
37%
49%
50%
56%
58%
81%
15%
21%
20%
20%
27%
32%
19%
33%
42%
35%
50%
54%
59%
57%
77%
Non Modeled Data Exploration And…
Streaming Analytics
Advanced Visualization
Text Analytics
Metadata Generated Analytics
Predictive Analytics
Search/Interactive Discovery
Location Analytics
Process Analytics
Olap
Embedded Analytics
Performance analytics
Web Analytics
Dashboard
Reporting
2014
2012
“What is your firm's/business unit's current use of the following technologies?”
Source: Forrester Research
+62% 33. DEFINITION
FORRESTER
Software that can filter, aggregate, enrich, and analyze a high throughput of data from disparate live data sources to visualize business in real time, detect urgent situations, and automate immediate actions. 34. © 2014 Forrester Research, Inc. Reproduction Prohibited
34
We call these in-the-moment advantages:
#PerishableInsights
Insights that can provide incredible value but the value expires and evaporates once the moment is gone. 35. © 2014 Forrester Research, Inc. Reproduction Prohibited
35
Streaming analytics is only half about ingestion
›High-throughput, uneven ingestion of event, sensor, transactions and just about any periodic data that just flows unrequested
•Architectural concerns such as availability, scalability, and latency (performance) are handled by platform
•Connect to multiple live disparate data sources
35
36. © 2014 Forrester Research, Inc. Reproduction Prohibited
36
The distinguishing magic of streaming analytics is about streaming operators
›Simple and complex analytical operators
•Detect, filter, and/or aggregate events
•Lightweight transformations and enrichment
•Dimensional window operators (e.g. break a geofence, average pressure over 5 minutes)
•Temporal pattern detection (e.g. if A and then B within 2 seconds)
36
38. © 2014 Forrester Research, Inc. Reproduction Prohibited
38
The constructs of streaming applications are different from conventional applications…
Filtering
Aggregation/correlation
Enrichment
Location/motion
Time windows
Temporal patterns
Familiar
Unfamiliar 39. © 2014 Forrester Research, Inc. Reproduction Prohibited
39
Data Warehouse
Analytics
Historical
…and, so is the application architecture
Push notifications
Email alerts
HTML5
Dashboards/
visualizations
APIs
Streaming
Analytics Application Platform
Stream 2
Backend Database
Traditional App
API calls/responses
Stream 1
Stream 3 40. © 2014 Forrester Research, Inc. Reproduction Prohibited
40
Streaming analytics platforms enable a whole new class of applications
›Detect , adapt, and act applications require high- performance data access on the front-end and the back- end.
›Provide development tools to create streaming applications
›Reduce development time by simplifying the architectural concerns of performance, scalability, and availability. 43. © 2014 Forrester Research, Inc. Reproduction Prohibited
43
If you can measure it and it’s connected to the Internet, then you can use it 44. © 2014 Forrester Research, Inc. Reproduction Prohibited
44
Ubiquitous computing
Everyware
Ambient intelligence
Smart world
Connected world
Cognitive computing
Pervasive computing
Physical computing
Context-aware pervasive systems
Machine-to-machine
Industrial Internet
Internet of everything
Thingternet
Sensor revolution 47. © 2014 Forrester Research, Inc. Reproduction Prohibited
47
Lots of streaming data is cloud born
›Mobile, web and IoTdata
›Elasticity of architecture can handling the spikeynessof both ingestion and streaming operator compute
›Lower-latency integration with other services to enrich streams from database, data warehouses 50. © 2013 Forrester Research, Inc. Reproduction Prohibited
50
Thinking in streams requires new technology and mindset
›Data silos hinder visibility and prevent streaming insights.
›Big Data strains the ability of legacy technology to delivery handle large, uneven flows of data
›Predictive and streaming analytics capabilities are lacking or non-existent
›There’s a lack of external and contextual data sources that enrich data.
›Developers still think in request/response 53. © 2014 Forrester Research, Inc. Reproduction Prohibited
53
Streaming analytics can uniquely enable three new tiers of app functionality
Source: April 22, 2014, “Use Sensors To Take Apps To The Next Level Of Customer Engagement” Forrester report 54. Stop
What if you knew your customer was near your store on a sunny day? 55. © 2014 Forrester Research, Inc. Reproduction Prohibited
55
NFL
Sensors in every players’ shoulder pads will change the way we analyze and watch the game 59. Trip
2
Buy a shut-off valve for the copper tubing. 60. Trip
3
Buy a T-connector to tap the cold water supply line. 62. Trip
5
Finally. A special drill bit to make a hole in the kitchen floor for the copper tubing. 64. © 2014 Forrester Research, Inc. Reproduction Prohibited
64
Design principles for customer –facing streaming apps
›Learning who the customer really is
›Detect the customer’s intent in-the-moment
›Adapt functionality and content to match intent
›Optimize for the device (human-computer interface) 68. What kinds of apps could youdevelop if could predict, detect and adapt to what is happening in your business in-the- moment?