big data analytics 101: how to use it to your advantage
DESCRIPTION
Big Data Analytics 101: How to use it to your advantage We’re living at the dawn of the age of big data…such vast quantities of information from so many sources that organizations are only beginning to ponder how to process, manage, and make the most of this seemingly bottomless well of knowledge. Big data sources—from social networks to mobile devices and remote sensors—are touching more people every day and businesses need to know how to translate that data into actionable decision making that influence events. What role does, or will, big data play in your organization? Tap into the key trends, common myths, and driving forces behind this revolution and the business intelligence and analytic tools that can help you use it to your advantage. We’ll examine: • The biggest myths about big data • How technology is evolving to support better decision making • New ways to gather, process, and consume data • The risks involved • Why you should careTRANSCRIPT
© 2014 Tangoe, Inc.
Presented by:
Troy Fulton, Director, Product Marketing
February 20, 2014
Big Data Analytics 101:
How to Use It to Your Advantage
© 2014 Tangoe, Inc.
Today’s Speaker
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Troy Fulton
Director, Product Marketing
• 20+ years in high-tech and communications devices
• Senior product marketing and management positions with global
corporations including Motorola Mobility, Nokia, and Compaq
• MBA from The College of William and Mary; BA from Boston
College
© 2014 Tangoe, Inc.
Agenda
• Definitions
• Why Pursue Big Data?
• Use Cases
• What is your Data Worth?
• Implementing Big Data
• Mistakes and Myths
• What’s Next?
• Q&A
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© 2014 Tangoe, Inc.
How Big is Big?
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© 2014 Tangoe, Inc.
Definitions – What is Big Data?
• Big Data is When…
– Require cost-effective, innovative
forms of information processing for
enhanced insight and decision making
• Volume
– Apply the 80/20 rule
> 160 TB of unstructured content
Smaller companies: ~ 11TB
• Velocity
– High rate of change (consumption
or change)
– Requires fast analysis
• Variety
– Format, structure, content, language
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© 2014 Tangoe, Inc.
Big Data – What is it Not?
• Big data = Big $$ = Confusion
– Many technologies are not new
• Not just about volume
– Issue when quantity exceeds
capacity
• Not only Hadoop and MapReduce
– There are alternatives
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© 2014 Tangoe, Inc.
Why Pursue Big Data?
• Deliver against a business
objective
– Payoff is not technical or
predict
– How can the firm influence?
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© 2014 Tangoe, Inc.
Predictions and Use Cases
• $17B industry in 2015
– Big data technology and services
– 40% CAGR
IDC
• Networked firms have an edge
– Leverage data and business analytics
– Web-based data exchange
McKinsey
• Strategic Planning
– 2015: 50% of Big Data solutions utilize
data streams from devices, apps, people
– 2016: 30% of companies monetize their
information assets
Gartner
• Use case examples:
– A bank visualizes patterns to detect fraud
– Doctors determine best protocols
– Auto manufacturers see the core cause
of production delays
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© 2014 Tangoe, Inc.
Big Data Analytics
• Analytics are not new
– IBM 360 mainframes had DSS
• 2016: $50B (IDC)
– Driver: Big Data
– $232B spent on analytics 2012 – 2016
Gartner
• 25% of employees access analytics tools
– Analytics will be pervasive
– Integrated into legacy and new
applications
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© 2014 Tangoe, Inc.
Analytic Tool Buckets
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© 2014 Tangoe, Inc.
Why Big Data Analytics Will Be Pervasive
• Process Improvement
– Streamline Inter-related business activities
– Data-based evidence enables confident choice selection
– Supports continuous improvement
• Intelligent Events
– Trigger-based applications
– Adaptation process and/or policy enforcement
• Contextual Relevance
– Role-based data dashboards
– Customized by user, device, application management
and connection type
• Analytical Insight
– Understand the “how” and “why”
– UX is critical path
•
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© 2014 Tangoe, Inc.
Implementing Big Data Analytics
• Business requirements
– Who / what is driving requirements?
– Business case? Use cases
– Define capabilities and analytic process flows in a business context
– Scope identifies decision points within the process
– Example: collaborative demand and supply forecasting and planning.
Requires analytical capabilities and insight integration multiple business functions
• Define your data sources and context
– Where are they? What are they?
– What’s the best way to reach and replicate them when required?
• Create a proof-of-concept
– Evaluate BI technology in terms of data visualization
• Performance, security, and data governance
– Overlook at your peril for a successful implementation
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© 2014 Tangoe, Inc.
Avoiding Failure
• 85%
– Fortune 500 organizations will fail to exploit big data for competitive advantage
(Gartner)
• Understand before judgment
– Analytical outputs may threaten management
– Ensure technical and business leaders trust analytical outcomes
– Depersonalize and create a shared sense of purpose impact on business
objectives
• Who drives?
– Business leaders drive business problem identification and priority
Truth as a variable
– IT as ecosystem contractor
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© 2014 Tangoe, Inc.
Avoiding Failure
• Project scoped too large
– Waterfall approach may not yield value
– Consider an agile approach
Iteration reviews deliver solution
– Bring ‘n brag accomplishments
– Gap analysis
What’s working…roadblocks…and recommendations
– Creates a team sense of purpose and executive investment
– Course correction opportunities sooner
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© 2014 Tangoe, Inc.
Mythical Confrontation
• Math degree only
– Complexity in implementation is a software challenge, not a user problem
– Data and insight output customized by data-savvy information worker
– Mathematic algorithms not required
• Long time-to-value
– The Past: Traditional BI and predictive analytics as an experiment
High human and software CapEx, and opportunity cost
– Today: Identify the top 3 correlation attributes that convert lead into a sale?
What are the best segments to test offers?
Based on data traffic patterns, can we reduce or purchase infrastructure on-demand?
No longer back-room, need-to-know, top-down
• Incomprehensible results
– Not confined to coefficients, p-values
– Example: bar charts illustrate patient’s likelihood of re-admittance based on correlated
factors
Based on 10 years of research, 500,000 people with similar profiles, in North America
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© 2014 Tangoe, Inc.
What’s Next?
• Need a strategy to improve business processes and outcomes
– Combine people, process and platforms
– Measurable performance targets
– Business and IT leaders have a shared sense of purpose
– Align with business objectives
• Big Data Enhancements
• BI vendors offer embedded data but require proprietary hardware appliances
• Look for DaaS solutions in 2014
• Mining multichannel engagement data to better predict
• Mobile (and embedded) BI
– Empowered employees conduct real-time analysis anywhere, authorized devices
– Consumerized UX drives self-service exploration of what matters to them most
– Mobile revolutionizes how information is distributed throughout the enterprise
• Social Enterprise
• Collaborate, adjust, optimize….from insights generated along the business process journey
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© 2014 Tangoe, Inc.
Questions and Contacts
Troy Fulton
Director Product Marketing
Tangoe
+1.203.859.9300
www.tangoe.com