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Big Data Discovery & Other Key Analytics TrendsTimo Elliott, VP Innovation Evangelist SAP
@timoelliott
Analytics is the #1 Spending Priority for 2015 and beyond
Rank Technology 2014 2015
1 BI/Analytics 50% 41%2 Infrastructure and Data Center 37% 31%3 Cloud 32% 27%4 ERP 34% 26%5 Mobile 36% 24%6 Digitalization / Digital Marketing 11% 17%7 Security 11% 13%8 Networking, Voice, and Data
Communications12% 12%
9 Customer Relationships 8% 11%10 Industry-Specific Applications 10% 9%
Gartner: Top 10 CIO Spending Priorities 2015@timoelliott
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Analytics Took Over The World…
@timoelliott
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By 2020, information will be used to
reinvent, digitalize, or
eliminate80%of business processes and
products from a decade earlier.
From The Back Office To The Business Models of Future
”
“
@timoelliott
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The Third Era of Information Technology
IT Craftsmanship IT Industrialization Digitalization
IT provides innovations and new
capabilities
IT supports efficiency, effectiveness, and
integrity
Engage
Offer
Monetize
Adapt
Create
Ideate
Digital provides continual opportunities for growth, innovation,
and differentiation
@timoelliott
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By 2020 data monetization efforts will result in enterprises pursuing digital transformation initiatives increasing the marketplace’s consumption of their own data by more than
100x
More Business Means More Data
”
“
Source: IDC Big Data and Analytics FutureScape 2015@timoelliott
Enterprise Data Remains One of The Top Strategic Projects
IDC Futurescape: Worldwide CIO Agenda 2015 Top 10 Decision Imperatives@timoelliott
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The Rise of the Chief Data Officer“The CDO is a senior executive who bears responsibility for the firm's enterprise wide information strategy, governance, analytics control, policy development, and effective exploitation.”
@timoelliott
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Information Is Money
By 2016, 30% of businesses will have begun directly or indirectly monetizing their information assets via bartering or selling them outright. .
– Gartner 2015
”“
@timoelliott
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Convergence
Big Data
Planning
Data Science
Data Discovery
Cloud Analytics
Executive Dashboards
@timoelliott
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Big Data On The Gartner Hype Cycle
Source: Gartner, August 2014
Innovation trigger
Peak of Inflated Expectations
Trough of Disillusionment
Slope of Enlightenment
Plateau of Productivity
Big Data
@timoelliott
12© 2015 SAP SE or an SAP affiliate company. All rights reserved.
Big Data Discovery=
Big Data
Data Discovery
Data Science
Gartner Strategic Planning Assumption: By 2017, Big Data Discovery Will Evolve Into a Distinct Market Category
@timoelliott
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Big Data Discovery
• Volume, velocity, or variety of data
• Potential business impact
• Difficult to implement• Potentially expensive• Lack of skills available
• Ease of use• Agility and flexibility• Time-to-results• Installed user base
• Complexity of analysis• Potential impact• Range of tools• Smart algorithms
• Difficult to implement• Slow and complex• Narrow focus of
analysis
• Limited depth of information exploration
• Low complexity of analysis
BIGDATA
DATASCIENCE
DATADISCOVERY
@timoelliott
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Big Data Discovery
• Simpler to use than data science
• Accessible to a wider range of users
• Broad range of data manipulation features
• Able to handle new types of data sources
• With adequate performance for big data
BIG DATA
DISCOVERY
@timoelliott
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Potential impact per
user
Potential user base
The Rise of the Citizen Data Scientist?
Business analyst
Data scientist
Citizen data
scientist
@timoelliott
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Prescriptive Analytics
“By 2020, 50% of all business analytics software will include prescriptive analytics built on cognitive computing functionality”
IDC FutureScope 2015@timoelliott
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Centerpoint Energy
@timoelliott
@timoelliott
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SAP HANA VoraWhat’s Inside and What Does It Do?
DemocratizeData Access
Make PrecisionDecisions
SimplifyBig DataOwnership
SAP HANA Vora is an in-memory query engine which leverages and extends the Apache Spark execution framework to provide enriched interactive analytics on Hadoop.
Drill Downs on HDFSMashup API
EnhancementsCompiled Queries
HANA-Spark AdapterUnified LandscapeOpen Programming
Any Hadoop Clusters
“By 2020, 90% of databases (relational and non-relational) will be based on memory-optimized technology”
IDC
@timoelliott
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YARN
HDFS
Other Apps
Files Files Files
HANA-Spark Adapter for improved performance between distributed systems
Compiled queries enable applications & data analysis to work more efficiently across nodes
Familiar OLAP experience on Hadoop to derive business insights from big data such as drill-down into HDFS data
Compiled Queries
Spark Adapter
Drill Downs
SAP HANA in-memory platform
Vora
Spark
Vora
SparkIn-Memory
Store
Application Services
Database Services
Integration Services
Processing Services
Vora
SparkHANA-Spark
Adaptor
HANA Smart Data Access, UDFs, Others
Extensive programming support for Scala, python, C, C++, R, and Java allow data scientists to use their tool of choice,
Enable data scientists and developers who prefer Spark R, Spark ML to mash up corporate data with Hadoop/Spark data easily
Optionally, leverage HANA’s multiple data processing engines for developing new insights from business and contextual data.
SAP HANA VoraBringing Business to Big Data
@timoelliott
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Bringing it All Together
ETL DW Q&R, Data
Discovery
Predictive Planning Other (spatial,
etc.)
Data Visualization
Operational Reporting
Enterprise Data Big Data
@timoelliott
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SAP Cloud for Analytics
All Analytics. One Product.
All-embedded People-centric Enterprise-class
@timoelliott
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#AskSAP Call on December 1st
Cloud Analytics
@timoelliott
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But…but… but…Security! Think Again
Many enterprises are paying an opportunity cost by allowing unwarranted security fears to inhibit their use of public cloud services that would be more secure, and more agile, than processes they implement within their own data centers.
– Gartner: Top Strategic Predictions for 2016 and Beyond
”
“
@timoelliott
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 27
Analysts Becoming Strong Proponents of Cloud
Recent history has shown that virtually all public cloud services are highly resistant to attack and, in the majority of circumstances, represent a more secure starting point than traditional in-house implementations. No significant evidence exists to indicate that commercial cloud service providers have performed less securely than end-user organizations themselves. In fact, most available evidence points to the opposite.
– Gartner: Top Strategic Predictions for 2016 and Beyond
”
“
@timoelliott
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 28
On-Premise Analytics Isn’t What It Used To Be…
“We found, on average, that 45% of the data business people use resides outside of the enterprise BI environments.
An astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications.”
Source: Forrester
In enterprise sys-tems
Not in enterprise system
55%
45%
@timoelliott
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Others Are Investing
36%Already replaced or planning to replace
with SaaS BIwithin the
next 2 years
Source: "Application Adoption Trends 2015: The SaaS Boom Continues As Businesses Demand Agility“. Forrester
31%Already complementing or planning to complement
with SaaS BI within the
next 2 years
“Through 2020, spending on cloud-based big data and analytics technology will grow 4.5x faster than spending for on-premises solutions”
IDC Futurescape 2015
@timoelliott
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The Opportunity
New Business Opportunities
Traditional Analytics
Data Value
Volume / Variety / Velocity of Data
@timoelliott
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“Intricate calculations of sales by territories will appear as if by magic in the digital age ahead”
@timoelliott
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Project Cybersyn: “devolve decision-making power within industrial enterprises to their workforce in order to develop self-regulation of factories.”@timoelliott
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Decision Cockpits
@timoelliott
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Multi-Screen Decision Making
@timoelliott
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Data Discovery and Self-Service Analytics
“Through 2020 spending on self-service visual discovery and data preparation market will grow 2.5x faster than traditional IT controlled tools for similar functionality”
IDC@timoelliott
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Culture Clash Around Analytics
Internally-orientedCosts
GovernanceEfficient reuse
Customer-facingOpportunitiesFlexibility & speedExperimentation
IT Business
@timoelliott
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Culture: Suits AND Hoodies
Source: Gartner@timoelliott
Design Thinking
@timoelliott
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Ethics & Privacy
@timoelliott
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Convergence
Big Data
Planning
Data Science
Data Discovery
Cloud Analytics
Executive Dashboards
@timoelliott
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 42@timoelliott
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Thank You!
Timo ElliottVP, Global innovation Evangelist
[email protected]@timoelliott