Download - Big data analytics 101: How to use it to your advantage

© 2014 Tangoe, Inc.

Presented by:

Troy Fulton, Director, Product Marketing

February 20, 2014

Big Data Analytics 101:

How to Use It to Your Advantage


Today’s Speaker

2

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


Agenda

• Definitions

• Why Pursue Big Data?

• Use Cases

• What is your Data Worth?

• Implementing Big Data

• Mistakes and Myths

• What’s Next?

• Q&A

3


How Big is Big?

4


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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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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Why Pursue Big Data?

• Deliver against a business

objective

– Payoff is not technical or

predict

– How can the firm influence?

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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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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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Analytic Tool Buckets

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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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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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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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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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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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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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Questions and Contacts

Troy Fulton

Director Product Marketing

[email protected]

Tangoe

+1.203.859.9300

[email protected]

www.tangoe.com

mailto:[email protected]

Download - Big data analytics 101: How to use it to your advantage

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