As business becomes more self-sufficient in accessing and putting data to work for analytics, there are many steps that are circumvented that can jeopardize the quality of business decisions. While it might seem easy to do one-off data preparation cycles that create analytic silos, the importance of placing governance on the data and users is essential to ensure accuracy of information used by business. The solution for these challenges can be addressed by applying effective processes and systems that are shared across business and IT. In this presentation, you'll will learn the latest best practices and steps to increase data governance and preparation processes that will shorten the time to efficiently connect users and data at any time

1. © 2016 Ventana Research1 © 2016 Ventana Research
Governing and Preparing Data
for Analytics and Business
Information Builders Summit - June 14, 2016
Mark Smith - CEO & Chief Research Officer

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Digital Data All Over Planet Earth

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New Generation of Information Assets

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Data is Center of Analytics

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Data Required Across Business Personas
The following usage roles operate across
business that require data:
Information Consumers
• Digest information and perform basic
interactions
Knowledge Workers
• Utilize and interact analytics to drive actions
and decisions.
Designers
• Enable the design and use of information
across roles.
Analysts
• Mashup data and design analytics to provide
foundational insights for business.
Data Geeks
• Enable big data to be exploited in an immature
world through Data Scientists.
IT and Business Intelligence Experts
• Utilize the tools to provide secured access to
data and related analytics and metrics.

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Harmony in Discovery Requires Confidence

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Discovery Requires Accurate Data

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Breadth of Analytics Requires Quality Data
Related research facts:
•Range of analytics are needed
to meet the usage personas.
•Predictive analytics ranks
number five in analytic
capabilities currently available in
the organization (57%), lagging
more descriptive approaches of
query and reporting (74%)
•Visual analytics is used for
contextual understanding (48%)
and root cause analysis (40%)
Source: Ventana Research Big Data Analytics Benchmark Research
18%47%
Advanced /
predictive
26%13%
Descriptive
analytics
20%16%
Real-time
analytics
13%9%Visual Analytics
In-database
analytics
In-memory
analytics
SecondFirst
Importance
15%9%
7%4%

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Range of Data Tasks are Required
Additional Data Tasks:
•Top five data activities are
essential but others like
auditing, loading,
synchronized, metadata and
transforming are important to
28 to 25 percent of
organizations.
•Preparing data is required
according to 27 percent of
companies but many other
tasks are a higher priority.
53%
52%
45%
44%
36%
To integrate data in both your enterprise and the
cloud, which data activities are required?
Analytics
Quality of Data
Security
Accessing
Extracting
Source: Ventana Data and Analytics in the Cloud Benchmark Research

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But Analysts Waste Time on Data Tasks
Largest time spent on data related tasks:
Preparing Data for
Analysis
55%
Reviewing data for quality and
consistency
48%
Determine how
changes impact
business
21%
Trying to determine root
cause of situation
27%
Waiting for data and information
from IT
28%
Source: Ventana Research Data and Analytics in the Cloud Benchmark Research

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Spreadsheets and Managing Data?
Unreliable Technology
• Swirl of spreadsheets
challenge business.
• Little confidence in the
accuracy of data.
• Almost half of business
export to integrate.
• Wasted time preparing
and presenting data.

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Big Data Brings Governance Challenges

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Big Data Demands Continues to Expand
Source: Ventana Research Information Optimization Benchmark Research
94%
of organizations intend to use big data.
23% have used for more than a year
56% have started deploying in past 12 months or will begin
to use within the next 12 months
45%
of organizations are either using
Hadoop or plan to use Hadoop over the
next year.
Another 26% are still evaluating the technology

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Big Data in Cloud is Diversifying Rapidly
Related Research:
• Growth is distributed
across many
categories.
• Establishment of
NoSQL and growth of
in-memory noted as
part of research.
22%50%RDBMS
25%37%Flat files
26%37%
DW
Appliance
Hadoop
In-Memory
Databases
NoSQL
Current
Deployment
31%12%
34%24%
29%12%
Source: Ventana Research Data and Analytics in Cloud Benchmark Research
Plan in Next 24 Months
Specialize
d DBMS
24%10%

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Frequency of Big Data is Reality
Related research facts:
•Nearly a one-in-four companies
integrate data into big data
stores in Real time, whereas, a
one-in-three businesses do it
Every day.
o Midsize (44%) companies
integrate data every day,
whereas.
o Data is integrated every day
by Services (40%) segment,
whereas, Manufacturing
(19%) integrates every hour.Source: Ventana Research Big Data Integration Benchmark Research
24%
16%
7%
30%
9%
Real time
Every hour
Every day
Weekly
Monthly
How often does your organization need to
integrate data into your big data store?

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Big Data is Shifting to Real Time
Source: Ventana Research Big Data Integration Benchmark Research
43%
integrate event-centric data to big data.
28% integrate network traffic and monitoring.
41%
state relevance of Internet data sources.
Another 25% indicate relevance of location sources.
19%
state importance of Sensor & RFID data.
Another 17% indicate relevance of Internet-based event
cloud.

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Big Data Creates Deluge of Challenges
© 2015 Ventana Research17

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Big Data has Larger Data Challenges
1. Reviewing data for quality and
consistency (52%)
2. Preparing data for integration (46%)
3. Connecting to data sources (39%)
4. Deploying integration tasks (36%)
5. Designing tasks for integration (35%)
Source: Ventana Research Big Data Integration Benchmark Research

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Examine New Approaches to Data
Assess Environment
• Only one-third of
organizations are satisfied
with their current
technology.
• More than half of
organizations said their
current infrastructure is not
fast enough or flexible
enough; almost half said
the technology is simply
inadequate.
• About half of organizations
turn to their existing
database or data
integration vendor.

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Challenge of Effective Big Data Integration
Inefficient Processes
• Use data-based business
insights improves
competitiveness.
• Our research finds that more
than half (55%) of
organizations are only
somewhat confident or not at
all confident in their ability to
process large data volumes.
• Even more (58%) doubt their
ability to process data that
arrives at high velocity.

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Sensor
Technology
Event
Orientation
Industry
Standards
Fast and
Big
Data
Advanced
Analytics
Security and
Privacy
“The Internet of Things (IoT)” Shift

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Internet of Things has Business Potential

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Internet of Things: Machines and Devices

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Analytics Shifting to Information Assets
© 2016 Ventana Research
9

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Data is Foundation for Analytics
Data
Model
Access
Analytics
Discovery
Integrate
Predict
Communication
Collaborate
Manage
Inform
Act
Automate

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Effective Evaluation of Analytics & Data
Download Executive Summary
http://www.ventanaresearch.com/BIValueIndex/

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Empower Analysts to Architect Data

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Establish Process for Consistent Data
Improve Efficiency
• Enable personas with set of
tools to support information
value chain to exist.
• Publish methods to
transform data to meet
business standards.
• Identify and implement
means to automate data
preparation needs of
business.

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Governing Data Assets as Librarians

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Next Steps for Governing Data
1. Assess the processes and time
spent on preparing data to save
resources and time.
2. Avoid creating silos of data
processes that could prepare
the quality of data differently.
3. Determine the tools and
methods to better manage the
data requirements of business.
4. Assemble a committee from
across LOB that represent the
needs and methods required.
5. Prioritize business and IT
investments to support data
for analytics and operations.

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Q&A

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Contact Information
Twitter
@marksmithvr and @ventanaresearch
LinkedIn
http://www.linkedin.com/company/ventana-research
Analyst Perspectives
http://marksmith.ventanaresearch.com
Community and Web Site
http://www.ventanaresearch.com

33. © 2016 Ventana Research33 © 2016 Ventana Research
Governing and Preparing Data
for Analytics and Business
Information Builders Summit - June 14, 2016
Mark Smith - CEO & Chief Research Officer