Data & Analytics Platforms & Tools: Trends to Watch in 2016

© 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Data & Analytics Platforms & Tools
Continued growth in low-cost data store alternatives
IBM HorizonWatch 2016 Trend Report – External Version
Stacy Novack, Distinguished MI Professional, Manager, Market Development - Software Solutions
Craig Doyle, Senior Advisor, Analytics BU, Market Development, IBM
Bill Chamberlin, bluemine Product Manager, HorizonWatch
April 10, 2016

About This Trend Report
2 HorizonWatch Trend Report: Big Data & Analytics Platforms (External Version)10April2016
 Purpose: The slides provide an overview on Big Data & Analytics Platform trends
 Content: Summary information about the Big Data & Analytics Platform marketplace,
including trends drivers, spending trends and adoption challenges. Also included are
links to additional resources.
 How To Use This Report: This report is best read/studied and used as a learning
document. You may want to view the slides in slideshow mode so you can easily follow
the links
 Available on Slideshare: This presentation (and other HorizonWatch Trend Reports
for 2016) will be available publically on Slideshare at
http://www.slideshare.net/horizonwatching
 Please Note: This report is based on internal IBM analysis and is not meant to be a
statement of direction by IBM nor is IBM committing to any particular technology or
solution.

Low-cost computing generates more data than humans can readily
exploit, driving the move to analytics for business value extraction
3
Source: IBM MD&I HorizonWatch, TBR, Inc.
“While well-established products predominate
in the on-premise (on-prem) segment, the
public cloud segment is dominated by those
products commonly called NoSQL and by
Hadoop.” IDC: Worldwide Nonrelational Database
Management Systems Software Forecast
“Changes in the database world offer both
significant opportunities and acute threats to
the Database Development and Management
Tools software market. On the one hand, the
proliferation of new and different database
technologies cries out for tools to provide a
cohesive management environment. On the
other hand, sophistication in the mature
Relational DBMS space has resulted in more
internal self-management of those products,
closing doors for third-party tools suppliers.”
IDC: Worldwide Database Development and Management
Tools Software Forecast
Key Insights
1. Interoperability of databases. Rise of the data economy
dictates vendors build simple ways to ingest data from
multiple sources and form factors. It may also accelerate
database commodization, threatening legacy database
vendors
2. Rise of low-cost data store alternatives (Hadoop,
Cloudera, Spark). Legacy analytics vendors relying on
data warehouse licenses for their monetization will face
rapid decline as services companies shift data to lower-cost
data storage configurations.
3. Users demand improved experience. IT has a backlog of
legacy apps in need of UI modernization and lack the skills
on staff for rapid deployment.
4. Cloud adoption/consumption. Cloud adoption passes
peak confusion. Vendors consolidate and IT needs help with
the transformation.
5. Winning the developer. Developers flock to container
technology, seeking simple configuration management
structures to rapidly push applications and updates.
Connections to competing platforms expand addressable
markets and accelerate commodization.
HorizonWatch Trend Report: Big Data & Analytics Platforms (External Version)10April2016

Analytics ingests data from multiple sources, commoditizing
databases and fueling IoT and systems of engagement demand
 Commoditization of the database layer. Multiple sources of
data feeds will be standardized to meet security and
compliance standards. Standardization weakens the “lock in”
value of legacy databases, allowing emerging databases with
cheaper operating costs opportunity to flourish.
 Move to hybrid cloud provides flexible location of data.
Software delivery cycle shifts require greater speed and agility
to reduce time to market. Systems of engagement have more
unpredictable consumption patterns best served by elastic
infrastructures.
 IoT and digital systems of engagement drive demand,
driving the need for distributed data. Moore’s Law lowers
computing cost for edge devices. Edge computing enables
bringing the apps to the data in low-cost stores, curbing the cost
of in-memory applications.
 User experience and Mobility. Users demand a more
consumerized user experience at work. Accelerating Application
platform and tools adoption requires building visual wrappers
that enable citizen analysts to exploit analytics technology
without the need for support from data scientists and be able to
do it on their mobile devices.
4
“Organizations are adopting cloud
for big data, self-service business
intelligence, and omnichannel
personalized customer engagement.
The ability to scale and shrink
quickly in a cost-effective manner is
enticing to both enterprise architects
and line-of-business executives who
demand faster and more agile data
capabilities.” Forrester: Cloud Data
Management Is Still Risky For Trusted Business
Data
“The DBMS market is transitioning
rapidly and profoundly as the
delivery of applications and DBMS
capabilities to users is redefined.”
Gartner: IT Market Clock for Database
Management Systems, 2015
Market Trends

Multiple data sources and cloud computing options enable new use
cases, but also challenge conventional governance techniques
 Predictive analytics. Growing perceived value of
predictive analytics and making those capabilities
more accessible and consumable to LOB users
 Emerging databases and data warehousing.
Growing options to collect, manage and store
available data. Expansion of Hadoop, Spark,
NoSQL commercialization for cost containment and
flexibility
 Data governance and integration. Increasing
demand for flexible integration and governance
capabilities. Proliferating data sources require
integration services to ready data for consumption,
and governance is required to manage and query
broader data stores.
 Content management. Inconsistent execution of
metadata tagging impeded early ECM selling efforts.
Machine learning compels user to reevaluate ECM.
Machine learning commercialization hinges on
simplifying the human procedures needed to build
strong ECM environments for analytics queries such
as eDiscovery.
5
“The landscape has dramatically shifted and there
are glimmers of more mature stand alone
applications to support and solve data stewardship
challenges and processes..” Forrester: Data Governance
and Data Management Are Not Interchangeable
“In the era of big data, enterprise data warehouse
(EDW) technology continues to evolve as vendors
focus on innovation and advanced features around
in-memory, compression, security, and tighter
integration with Hadoop, NoSQL, and cloud.” Forrester:
The Forrester Wave™: Enterprise Data Warehouse, Q4 2015
Market Trends
IBM

Drivers for Analytics Platform & Tools purchases vary by industry
6
Market Trends
• Financial Services: Financial services customers
use Platform & Tools software to drive improvements
to operations and process management.
• Healthcare: Healthcare customers use Platform &
Tools software to achieve faster analysis and
decision making and improve operations
management.
• Consumer Goods: Many consumer goods
customers have adopted Platform & Tools designed
to help them achieve short-term cost savings and
operational efficiencies, and are now moving to
higher-value, customer-oriented initiatives..
• Industrial: The industrial vertical is a driving
segment for BI accessibility on a mobile device.
• Energy: Energy customers purchase BI software
solutions to improve efficiency of operations and
processes and reduce operating expenses.
Forbes: How Big Data Is Changing Healthcare
MAPR: Top 10 Big Data Trends in 2016 for
Financial Services
“Big data analytics is poised to change the
maintenance services models across the
manufacturing sector.” Frost & Sullivan: Big Data
Analytics is Poised to Change the Maintenance Services
Models Across the Manufacturing Sector

Big data and analytics create complex security, data management
and organizational change issues
 Security. Security is a critical factor in the success of
Platform & Tools programs and must be addressed from the
start of any implementation.
 Business case/ROI. Enterprises want improved
productivity, revenue growth and TCO metrics
 Data Management. The top seven reasons these
solutions failed to meet customer needs relate to data
integration, cleansing, management, storage and access.
Vendors must provide these capabilities, particularly as
customers seek to increase utilization from external data
sources.
 Analytics skills in context of training, UI, integration.
While advanced analytic and design skills are important,
customers indicate data security, business acumen and
data integration skills as the top three skills most critical to
success.
7
“Data is the lifeblood of today's digital
businesses, but for economic and even
political gain, highly skilled cybercriminals and
malicious insiders are determined to steal it.
Meanwhile, customers around the globe have
become highly sensitive to how organizations
track, use, and store their personal data.” The
Forrester: The Data Security And Privacy Playbook For
2016
“The 3rd Platform continues to drive growth in
the data integration and access software
market. Organizations moving their
applications to the public cloud are recreating
silos of information that need to be integrated.
Big Data and analytics are driving the need for
data integration and access software to help
with data capture, cleansing, and preparation.”
IDC Worldwide Data Integration and Access Software Market
Shares, 2014: Year of Affirmation of Data Integration on the
3rd Platform
Adoption Challenges

Selected Analyst Websites and Resources
8
 Forrester: Business Intelligence Playbook / Analytics (search)
 Frost & Sullivan: Analytics (search)
 Gartner: Business Intelligence (Portal) / Analytics (search) /
Analytics Blog Posts (search)
 IDC: Big Data and Analytics (Portal) / Analytics Research /
Analytics Blog Posts
 International Institute for Analytics - http://iianalytics.com/
 TBR: BI and Analytics
Forrester: Webinar
Gartner: Predictive Analytics
Gartner: Transform Your
Business With IoT Analytics
“Advanced analytics is analysis of all kind of
data using sophisticated quantitative methods
such as statistics, predictive and descriptive
data mining, visualization and optimization for
forecasting and having insights into the future
trends.” MarketsandMarkets
Important Links
10April2016 HorizonWatch Trend Report: Big Data & Analytics Platforms (External Version)

Selected Media Websites and Resources
9
 CIO.com: Business Intelligence, Analytics (search)
 ComputerWorld: Business Intelligence / Analytics
(search)
 eWeek: Big Data Analytics Project Center /
Analytics (search) / Business Intelligence (search)
 Forbes: Data Driven / Analytics (search) / Business
Intelligence (search)
 Harvard Business Review: Analytics
 InformationWeek: Big Data Analytics / Business
Intelligence (search)
 InfoWorld: Analytics (search) / Business Intelligence
(search)
 MIT Sloan: Analytics & Strategy
 NY Times: Analytics (search) / Business Intelligence
(search)
MIT Sloan
eWeek
“Organizations need to manage how best to
filter the huge amounts of data coming from
the IoT, social media and wearable devices,
and then deliver exactly the right information
to the right person, at the right time.” David
Cearley, vice president & Gartner Fellow
“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: IDC FutureScape: Worldwide Big Data and Analytics 2016 Predictions
Important Links

Selected IT Vendor and Consultant Websites and Resources
10
 Accenture: Analytics / Analytics (search)
 Booz Allen: Analytics / Analytics (search)
 Deloitte: Analytics / Analytics (search)
 Google: Analytics / Analytics (search)
 HP: Analytics / Analytics (search)
 IBM: Business Analytics / Big Data & Analytics /
Analytics (search)
 Infosys: Analytics / Analytics (search)
 Microsoft: Big Data / Analytics (search)
 Oracle: Advanced Analytics / Analytics (search)
 SAP: Analytics / Analytics (search)
 SAS: Analytics / Analytics (search)
 TCS: Analytics / Analytics (search)
 Wipro: Analytics / Analytics (search)
IBM
“Where customers are can be as
critical as who they are.” Google
“By 2018 most business users will have
access to self-service tools, but that only
one in 10 initiatives will be sufficiently
well-governed to avoid data
inconsistencies that negatively impact
the business.”Gartner
Important Links

Selected IBM Resources and Links
11
 IBM Analytics website
 IBM Watson Analytics
 IBM The Big Data & Analytics Hub
 Software: Cognos / Business Intelligence / Data
Warehousing / Customer Analytics / Predictive
Analytics / Social Media Analytics / Risk Analytics
 Global Services: Big Data & Analytics Consulting
 Government: Analytics Solution Center
 Research: Analytics and Mobile Enabled Solutions -
IBM Research India
 DeveloperWorks: Big data and analytics
 Institute for Business Value: Analytics Thought
Leadership
 Center for Applied Insights: Stories from data leaders
IBM Analytics website
“By applying analytic tools to business
transactions as they are occurring, the mainframe
systems can allow clients to have true “real-time”
insights.” IBM
Important Links
10April2016
“Three-quarters of survey respondents report that
their organizations are building out an optimized
data and analytics infrastructure capable of
responding to in-the-moment business needs.
More than two-thirds have expanded their use of
advanced analytics across their enterprise to more
precisely understand current business conditions
and customer behaviors.” IBM
HorizonWatch Trend Report: Big Data & Analytics Platforms (External Version)

Selected IBM Resources and Links
12
 Social Platform: Big Data & Analytics
Hub
 Facebook: IBM Analytics
 Twitter: @IBMAnalytics /
@IBMbigdata
 Twitter Hashtags #bigdata #analytics
 YouTube: IBM Analytics / IBM Business
Analytics
 Google+: IBM Analytics
 LinkedIn: IBM Analytics
 LinkedIn: IBM Big Data and Analytics
IBM Social Platform: Big Data & Analytics Hub
Important Links

More Insights on Technology Trends are Available
13
Other slide decks in this IBM HorizonWatch 2016 Trend Report series have been
posted to Slideshare
You are also invited to check out the following IBM websites and resources
– IBM Academy of Technology
– IBM Center for Applied Insights
– IBM Institute for Business Value
– IBM Research and Research News and 5 in 5
– IBM’s THINK blog

Data & Analytics Platforms & Tools: Trends to Watch in 2016

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