Big Data Analytics: Collecting, Analyzing and Decision Making



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Transcription:

Big Data Analytics: Collecting, Analyzing and Decision Making

Defining Big Data Jennifer Jones, Senior Indirect Sales Manager, CBTS

Thought Leader Definitions Oracle - Derivation of value from traditional, relational, database-driven business decision-making, augmented with new sources of unstructured data. Intel - Opportunities that emerge in organizations generating a median of 300 terabytes of relational data a week The Method for an Integrated Knowledge Environment (MIKE 2.0) Project - not a function of the size of a data set but its complexity... the high degree of permutations and interactions within a data set that defines big data. Definitions Summarized from The Big Data Conundrum: How to Define It? A View Column featured in MIT Review 10/3/2013

Characteristics of Big Data Large and complex data sets Require massively parallel software and servers Size presents numerous challenges. Biggest benefit is the additional information derivable from analysis Correlations produce important trends and predictive modeling.

The Four V s

Data Types Traditional Customer Data Prospect Data Warehouse Data Partner Data Unstructured Metadata Tweets Social Media Posts Multi-Structured Sensor Data Web Log Data

Why is Big Data Important? Business Analytics Without Analytics, Big Data is just noise

Panelists Suzanne Plesha Big Data s Impact on Marketing Assistant Director for the Center for Digital Marketing Advancement (CDMA) Kristina Bolin Big Data in Healthcare Project Manager for Humana Pharmacy IT Gretchen Loss Big Data and Analytics in Crime Analysis Director of Solutions Architects for Raytheon

Big Data s Impact on Marketing Center for Digital Marketing Advancement

TOPICS: What is Data-Driven Marketing? What are the Challenges? Best Practices

THEN: MARKETERS USED DATA What did people buy? Where did they buy it? Photo Courtesy: www.homepage.ntlworld.com

NOW: DATA-DRIVES MARKETING What are people buying right now? Where are our customers? How can we motivate them? What is their current experience with our product? What environmental factors are affecting purchases? Photo Courtesy: www.homepage.ntlworld.com

DATA-DRIVEN MARKETING What is Data-Driven Marketing? What are the Challenges? Best Practices Photo Courtesy: www.homepage.ntlworld.com

DATA-DRIVEN MARKETING: Customer Journey Awareness Consideration Purchase Retention Advocacy Taken from How to Integrate Social Media Marketing with all of your Online Efforts, by Lee Odden, 2013 Social Media Success Summit

DATA-DRIVEN MARKETING: Customer Journey Pay Per Click Email Online Ads Social Ads Reviews Blog Media Website Community Forum Social Networks Blog Awareness Consideration Purchase Retention Advocacy PR Radio TV Print Work of Mouth Email Direct Mail Ecommerce Store FAQ Knowledge Base Promotions Taken from How to Integrate Social Media Marketing with all of your Online Efforts, by Lee Odden, 2013 Social Media Success Summit

THE CUSTOMER IN CONTROL What is Data-Driven Marketing? What are the Challenges? Best Practices Photo Courtesy: www.empowermm.com

AUTHENTICITY Product Product Reviews Reviews What is Data-Driven Marketing? What are the Challenges? Best Practices Photo Courtesy: fonolo.com

COMPANY STRUCTURES What is Data- Driven Marketing? What are the Challenges? Best Practices Photo Courtesy: wikipedia.org

A 360 VIEW OF CUSTOMER What is Data-Driven Marketing? What are the Challenges? Best Practices Photo Courtesy: Retail TouchPoints/Teradata

REAL TIME ATTENTION What is Data-Driven Marketing? What are the Challenges? Best Practices Photo Courtesy: www.decodedfashion.com/tag/burberry

CREATE A NEW COMPANY CULTURE What is Data-Driven Marketing? Execute What are the Challenges? Best Practices Evolve Evaluate Photo Courtesy: www.topnews.com

THANK YOU Center for Digital Marketing Advancement Ball State University www.bsu.edu/mtech 765.285.0123

Big Data in Healthcare Kristy Bolin, PMP, CPCU

Big Data is a BIG DEAL in Healthcare There are an estimated 50 Petabytes of Data in the Healthcare Realm 1024 kilobytes=1 megabyte 1024 megabytes=1 gigabyte 1024 gigabytes=1 petabyte 1024 petabytes= 1 exobyte 1000 exobytes= 1 zettabyte 1000 zettabytes=1 yottabyte

What s the BIG DEAL about BIG DATA? 1. It enables more informed decision making and enhanced quality of care 2. It saves lives through remote consultation, whether urgent or diagnostic. 3. It creates more efficient, convenient and more cost effective delivery of care 4. It facilitates earlier and more accurate diagnosis 5. It provides greater and faster access to a patient s medical history reducing the risk of negative drug interactions or poor response to a course of treatment.

What s the BIG DEAL about BIG DATA? 6. It improves administrative efficiency and coordination 7. It allows rural residents to receive expert diagnosis and treatment from distant medical centers 8. It increases the timeliness of treatment and decreasing transfer rates while reducing medical costs through video technology 9. It supports real time treatment by first responders through the use of wireless devices 10. It enhances senior wellness and preventative care through telemedicine and remote in home monitoring.

The Good News The US faces a shortage of 140,000-190,000 people with analytical expertise and 1.5 million managers who can make decisions based on the analysis of big data

Key Metrics for the Healthcare Industry 1. Clinical Applications 2. Financial Applications 3. Operational Applications

Big Data and Analytics in Crime Analysis Gretchen Loss Director, Raytheon Cyber Products

Velocity Variety Volume BIG DATA Veracity The Dimensions of Big Data

The Analytical Cycle Planning and Direction Dissemination Collection and Management Analysis and Production Processing

Data Mining

Finding the Focus

Link Analysis

Social Network Analysis

Telephone Toll Analysis

Temporal Analysis

Geospatial Analysis

Visual Analysis Tools Rapidly piece together disparate data into a single cohesive intelligence picture. Identify key people, events, connections and patterns Increase understanding of the structure, hierarchy and method of operation of criminal, terrorist and fraudulent networks. Simplify the communication of complex data to enable timely and accurate operational decision making.