Más contenido relacionado La actualidad más candente La actualidad más candente (20) Similar a Big Data LDN 2018: THE NEXT WAVE: DATA, AI AND ANALYTICS IN 2019 AND BEYOND Similar a Big Data LDN 2018: THE NEXT WAVE: DATA, AI AND ANALYTICS IN 2019 AND BEYOND (20) Big Data LDN 2018: THE NEXT WAVE: DATA, AI AND ANALYTICS IN 2019 AND BEYOND2. 451RESEARCH.COM
©2018 451 Research. All Rights Reserved.
451 Research is a leading IT
research & advisory company
Founded in 2000
250+ employees, including over 120 analysts
1,000+ clients: Technology & Service providers, corporate advisory, finance,
professional services, and IT decision makers
85,000+ IT professionals, business users and consumers in our research
community
2,000+ technology & service providers under coverage
451 Research and its sister company, Uptime Institute, are the two divisions
of The 451 Group
Headquartered in New York City, with offices in London, Boston, San
Francisco, Washington DC, Austin, Mexico, Costa Rica, Brazil, Spain, UAE,
Russia, Taiwan, Singapore and Malaysia
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©2018 451 Research. All Rights Reserved.
Introducing the Data, AI and Analytics Channel
Data Platforms
Data Management
Data Science and Analytics
Artificial Intelligence
This channel formally expands our
previous data platforms and analytics
coverage to address artificial intelligence,
machine learning (ML) and deep learning
as strategic enterprise initiatives, as well
as enterprise blockchain.
451 Research has been covering AI and ML since
2001 – starting with text analytics and expanding to
audio speech, images, and video.
The new channel will enable more strategic focus on
the technologies and methods adopted by enterprises
to generate intelligence – both human and artificial –
from internal and external data. It will also show how
companies use this intelligence to drive competitive
advantage and generate new business opportunities.
+ Blockchain
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©2018 451 Research. All Rights Reserved.
Beyond Data, AI and Analytics
The Data, AI and Analytics Channel will not only drive our coverage of AI in the context of
data, AI and analytics products and services, but also how AI and the value of data – as well
as other data-related technologies – permeate all our research channels.
As such, Data, AI and Analytics Channel analysts will drive collaboration with our colleagues
in other channels, in particular Customer Experience and Commerce, the Internet of Things,
Information Security, Workforce Productivity & Compliance, Cloud Transformation, and
Applied Infrastructure & DevOps.
451 Research Channel Map
Datacenter
Services &
Infrastructure
Applied
Infrastructure &
DevOps
Managed
Services &
Hosting
Cloud
Transformation
Information
Security
Data, AI &
Analytics
Internet
of Things
Workforce
Productivity &
Compliance
Customer
Experience &
Commerce
Data,
AI and
Analytics
6. Data and Analytics, 2H 2018
Importance of Data
Q. Looking ahead 12 months, do you think data will be more important to your organization, less important, or
will there be no change 12 months from now?
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©2018 451 Research. All Rights Reserved.
Distribution of Hadoop ecosystem projects
HORTONWORKS
• Accumulo
• Calcite
• DataFu
• Druid
• Knox
• Phoenix
• Storm
• Tez
• Zeppelin
• Lizy
• Ambari
• Atlas
• Ranger
CLOUDERA
• Avro
• Flume
• Hue
• Impala
• Kudu
• Parquet
• Sentry
+ Cloudera Enterprise
BOTH
• MapReduce
• HDFS
• YARN
• Common
• HBase
• Hive
• Kafka
• Oozie
• Pig
• Solr
• Spark
• Sqoop
• Zookeeper
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Data warehouse/mart/lake
Logical Data Lake/Total Data Warehouse
Distributed Storage
Data Lake
Data
Warehouse
Data
Mart
Relational database
Data Warehouse
Data Mart
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Q8. Which of the following analytic database (data warehouse) vendors does your organization currently use?
1
4
44%
42%
33%
26%
15%
13%
10%
7%
6%
6%
5%
7%
Oracle
Microsoft
IBM
SAP
Cloudera
Hortonworks
Teradata
Pivotal (Greenplum)
MariaDB
Micro Focus (Vertica)
MapR
Other
% of Respondents (n=321)
Usage of analytic database(s)
Respondents whose organization currently uses an analytic database (data warehouse)
Source: 451 Research, Voice of Enterprise: Data and Analytics 2018
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©2018 451 Research. All Rights Reserved.
Source: 451 Research, Voice of the Enterprise: Information Security, Organizational Dynamics 2018
Q33. Which of the following security trends or buzzwords is the most overhyped? Please select no more than two.
1
6
Overhyped buzzword?
All respondents
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Source: 451 Research, Voice of Enterprise: Digital Pulse, Vendor Evaluations 2018
Q5. Which of the following technologies do you expect to have the most transformational impact on your organization’s
business operations by 2020?
1
7
Great transformational impact?
All respondents
52%
45%
41%
29%
14%
12%
9%
6%
6%
5%
4%
2%
2%
2%
4%
Cloud
Artificial Intelligence(AI) & Machine learning for Intelligent business applications
Mobile platforms and applications
Internet of Things (IoT)/sensor-based technology
Blockchain
Digital Assistants (e.g., AI-driven Bots)
Location-based technologies (e.g., beacons,Wi-Fi, video)
Biometrics (i.e.,voice,iris and fingerprint recognition for authentication)
Robotics
Augmented or VirtualReality (AR/VR)
Voice-activated Interfaces (e.g., Amazon Echo, Alexa, Siri)
3D printing
Drones
Other
Noneof the above
% of Respondents (n=1,130)
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“If you want immutable records chronologically linked
together in ‘blocks’ and you’re part of a trustless ‘chain,’
you’re going to love blockchain.
If not, the chances are that a more traditional distributed
database… is likely to fit your needs.”
4 51 R E S E A R C H
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©2018 451 Research. All Rights Reserved.
Being data-driven is
not without challenges
In order to become more data-
driven, enterprises need to invest
not only in new data processing,
analytics and machine learning
functionality, but also in more agile
approaches to data management
that reduce data friction and
accelerate time to insight.
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©2018 451 Research. All Rights Reserved.
Q4. Which of the following types of data does your organization analyze? Q19. What is your organization’s most significant barrier to using
data platforms and analytics?
2
2
Mo data, mo problems
The greater the number of data sources, the bigger data access and preparation headache
Source: 451 Research, Voice of Enterprise: Data and Analytics 2018
4.6
5.2
20%
29%
0%
5%
10%
15%
20%
25%
30%
0
1
2
3
4
5
6
All respondents Nearly all strategic decisions are data-driven
Average Number of Data Inputs Accessing and Preparing Data as a Significant Barrier
24. 451RESEARCH.COM
©2018 451 Research. All Rights Reserved.
A great deal of attention has been paid to catering to the first
three processes involved in AI and machine learning: data
collection, structuring, and modeling.
The last step, ensuring models are effectively operationalized,
has been somewhat neglected.
And yet placing machine learning models into production and
ensuring they remain effective is critical to successful data
science.
Operationalization
25. 451RESEARCH.COM
©2018 451 Research. All Rights Reserved.
Source: 451 Research, Voice of the Enterprise: Artificial Intelligence/Machine Learning 2018
Q14. What is your organization’s most significant barrier to using machine learning?
2
5
Most Significant Barrier to AI Adoption
Respondents currently using or planning to use AI/ML
36%
16%
15%
9%
3%
3%
2%
5%
10%
Not enough skilled resources
Accessing and preparing data
Limited budget
Deploying the results in operational systems
Algorithms inappropriate for our uses
Hard to build and maintain
Lack ofsupport/involvement fromsenior leadership
Other
None- wehave nobarriers to using machinelearning
% of respondents (n=207)
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©2018 451 Research. All Rights Reserved.
451RESEARCH.COM
©2018 451 Research. All Rights Reserved.
“The definition of
genius is taking
the complex and
making it simple.”
A L B E R T E I N S T E I N
27. 451RESEARCH.COM
©2018 451 Research. All Rights Reserved.
Vendors need to:
Open up machine learning to developers of all kinds
Understand the different skills and workflows needed in machine
learning versus traditional software development.
Get to grips with low-code services for less technical users.
Make machine learning more understandable – both to the end
users and the developers of machine learning-based applications.
Make making machine learning – and especially deep learning –
transparent enough so that developers can understand how a model
has come to its predictions.
Automation and the future of AI
27
28. 451RESEARCH.COM
©2018 451 Research. All Rights Reserved.
Data, AI and Analytics in 2019 and Beyond
Data Platforms
Data Management
Data Science and Analytics
Artificial Intelligence
The increasing convergence of ‘Hadoop’ and data
warehouse, and Industry-specific and cross-industry
enterprise blockchains going live
DataOps drives more agile data management
Increased focus on the ‘last mile’ of data science –
operationalization
The future of AI will be (more) automated &
explainable
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©2018 451 Research. All Rights Reserved.
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