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Big Data (Adv. Analytics) in 15 Mins. Peter LePine Managing Director – Sales Support IM & BI Practice
Big Data (Adv. Analytics) in 15 Mins.
Peter LePine
Managing Director – Sales Support
IM & BI Practice
Emtec, Inc. Proprietary & Confidential. All rights reserved 2013.
Agenda
• Big Data in 15 Mins.
• Goal: Provide a basic understanding of; What is Big Data; Why it’s important to
Customers; How Emtec can help identify Big Data opportunities.
What are Big Data & Adv. Analytics
How Organizations using Big Data
How Emtec can help
Emtec Overview
Big Data & Adv. Analytics Defined
Emtec, Inc. Proprietary & Confidential. All rights reserved 2013.
Big Data – Some real-world examples
• Retail Banking
–The expectedly large and negative consumer reaction to new fees announced by large US banks in
late 2011 is a case in point. Hundreds of thousands of accounts were lost in a few days—the
equivalent of a year of losses under typical market conditions—by the time consumer sentiment was
fully understood and corrective action could be taken.
–Hospitality Industry
• “Many airlines treat even their frequent flyers as strangers. We have the data to treat
them as they would want to be treated”
–EVP of British Airways
–Airlines & Hotels have acquired massive amounts of data via loyalty programs , and travel providers
have begun to analyze data in ways they hope will increase personalization.
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EPM
• Online Media
–“Analytics available to even the lowest YouTube channel producer now rival the most sophisticated reports CBS, NBC and ABC had available in the 1980s. Apply even better analytical engines to the data from Fitbit pedometers, Google Glass, Smartphones, etc. and you’ve got an unprecedented depth and breadth of knowledge available soon to anyone, anywhere.”
• James McQuivey is the author of “Digital Disruption: Unleashing the Next Wave of Innovation.” VP and Principal Analyst at Forrester Research.
Every day, we create 2.5 exaBytes of data — so much that 90% of the data in the world today has been created in the last two years alone.
2.5Xb = 2,500,000,000,000,000,000 (1018) Bytes of data
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Big Data – Some real-world examples
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Big Data Defined
• How BIG is Big Data???
–Social Media – Facebook reached 1 billion members in 2012
–Entertainment – Netflix has approx. 30 million subscribers
• Every download is 3 – 11 Gbytes
• Media – Many channels of 7*24 streaming media
–Twitter, LinkedIn, Yelp, MSN, and lots more
–Google Search – 1.2 Billion sites searched in 0.35 secs
• Corporate –Email, SMS & FTP sent / received per day
–2011 2012 2013 2014 2015
–105 110 115 120 125
• In 2011, the majority of Email & SMS users were; (Economist analysis)
–Asia Pacific accounts for 49%
–Europe accounts for 22%
–North America has about 14%
–Rest of World (15%) accounts for the remainder
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Data Mining Defined
• The ‘Engine’ of Advanced or Predictive Analytics
–Exploratory Data Analysis – An iterative exploration & filtering of the result-set
–Hypothesis Testing – Establish the conditions / filters , test / refine the validity of the Hypothesis
–Data Visualization – Heat Map or other representation of the distribution of the Dataset
• Real-world examples of Data Mining
–Social Media - Tracking of ‘Likes’ & ‘Dislikes’, reach out to Friends with similar interests
–Retail & Transportation – Pattern matching to develop pricing strategies based on time, usage, family
plans, etc.
–Insurance / Law Enforcement - Heat Map (Identify) based on more granular data than Zip code, more
granular time periods, etc.
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• Statistical function-based Analytics
–Aggregate a large Dataset of historical detail, filter out the ‘Noise” to Predict future; Trends / Behaviors
/ Events
–Analytical tools contain Libraries of Built-in Functions
–e.g. Business Functions – NPV, Depreciation, Compound Growth Forecast
–Statistical Models – Linear Regression, K-Factor, Probability modeling
• Real-world examples of Predictive Analytics
–On-line Retail – Select any Product… Product accessories (Associations)
–Hospitality – Pricing based on factors such as; Load / Occupancy, Loyalty & Competitor pressures
–Transportation – Predictive analysis to determine Route optimization, Maintenance schedules, Traffic
patterns
Big data analytics is done with Software Tools used as part of Advanced Analytics
disciplines such as Predictive Analytics and Data Mining.
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Predictive Analytics Defined
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The Language of Big Data & Predictive Analytics
• Terminology of Big Data & Predictive Analytics
–Data Warehouse Appliance – Parallel engine & Storage ‘packaged’ in a single device.
–Unstructured data – Any data that doesn’t conform to a Field or Column paradigm (e.g. a Document)
–MapReduce – Research project sponsored by IBM & Google to process very large datasets, in
massively parallel platforms (1,000’s of Nodes)
–Hadoop – Research project sponsored by Apache Foundation…
–NoSQL – Research project sponsored by UC Berkley & Rackspace…
–Statistical Analysis – Use of Statistical functions to Analyze & make data driven decisions from very
large Datasets
–Behavioral Analytics – Use of Behavioral (social sciences) functions…
–Pattern Recognition – Recognize patterns in very large Datasets…
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Summary - Big Data & Predictive Analytics
Big Data & Predictive Analytics should not be confused with “BI on Steroids”
Unique Platforms, Analytic Tools & Business usage.
Every Client needs some BI capability, whereas Big Data & Predictive Analytics are not on
the radar for smaller & mid-sized organizations.
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How Customers are using Big Data & Adv. Analytics
Emtec, Inc. Proprietary & Confidential. All rights reserved 2013.
Predictive Analytics
• Predictive Analytics isn’t the same as BI
–Business Specialist / Power User tools that predict future trends using Statistical Analysis techniques.
–Analytic Result-set is Prioritized / Ranked by frequency / probabilities etc.
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Target Clients / Industry Segments
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Retail Travel &
Hospitality
Financial
Services Media
High-volume Online &
Traditional Retail
Airlines, Hotels,
Timeshare, Rental
Cars, Travel
Retail Banking, Credit
Card, Insurance,
Brokerage
Mainstream Media
Specialized Channels,
etc.
• Growth Strategy
Use of Social media
Analyze & Predict trends
before competitors
Customer loyalty
• Growth Strategy
Customer loyalty,
Operational efficiencies
Partner Revenue
• Growth Strategy
Acquisition, no single
view of the customer
Customer retention &
Customer capture
Cross-sell & Up-sell
• Growth Strategy
Media transition to
subscription-based
News / Topic / Event
aggregation
Target A&P spend to
individual interests
• Customer Benefits
Right product, Right
location, Right price
• Business Benefits
Store Operations
Product associations
Improve Revenue &
Margins
• Customer Benefits
Customer care / loyalty
programs
• Business Benefits
Optimize Operations
Improve Revenue &
Margins
• Customer Benefits
Reduce Costs across
Products & Services
• Business Benefits
Patterns of behavior
Risk Analysis,
Improve Revenue &
Margins
• Customer Benefits
Narrow-cast News, no
longer Broadcast
• Business Benefits
Compete in a 7*24
Global Village
Group associations /
‘neighborhoods’
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Big Data & Predictive Analytics Landscape
Business
Intelligence Data Mining
Adv. Analytics
Structured
Databases ‘Big Data’
Infrastructure
Analytic Engine SQL / ODBC
or
Other Data Drivers
Unique Platforms, Analytic Tools & Business usage.
Some familiar names – IBM, Oracle, SAP & Microsoft
Many new names in what is a new & growing market segment
How Emtec can Help
Emtec, Inc. Proprietary & Confidential. All rights reserved 2013.
Custom Application
Development Services
• Information Delivery
–BI, reporting & analysis, advanced analytics &
‘Big Data’, KPIs, dashboards & scorecards,
business repository
• Information Management
–Data infrastructure, information as a corporate
asset
• Data Integration
–Extract, transform, load from data sources into
target DW or data marts
• Information Architecture
–Assessments, strategy, roadmaps & blueprints,
data architecture
IM & BI Practice Overview
Big
Data
Data Integration
Co
nte
nt
Man
ag
em
en
t
Master Data
DW Analysis &
Design
Data Governance
Data Quality
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Emtec Adv. Analytics Workflow
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Discovery
Pilot
Project
Technical
Impl.
Discovery Workshop or Assessment
• Understand functional (Business) requirements, and
• Understand the Data (Internal & External) Sources
• Develop a Strategic Roadmap for Analytics
Pilot Project & Project Planning
• Limited scope Pilot to test & validate hypothesis
• Build the business case for Implementation
• Prove the Technical Infrastructure (Tools & Data infrastructure)
Technical Implementation
• Refine & Filter Analytical results
• Develop Analytic reports
• Evaluate how the results Correlate to ‘real-world’ experience
Key Sales & Delivery Contacts
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Jamal Syed Deric Selchow
Sajid Patel Peter LePine
Delivery Management
Email: [email protected]
847-323-6588 (Mobile)
Sales Support
Email: [email protected]
408-674-7336 (Mobile)
OBIEE Practice Manager
Email: [email protected]
630-235-8393 (Mobile)
MSFT BI Practice Manager
Email: [email protected]
651-338-7507 (Mobile)
Emtec, Inc. Proprietary & Confidential. All rights reserved 2013.
Collateral specific to Big Data
• Sales Support Collateral
–Sales Briefing - Big Data in 15 Mins.
–Technical & Industry Case Studies
–Big Data Quick Reference Card
–Assessment Outline
• Marketing Collateral
–Industry Analyst Research papers
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