Analytics vs Statistics the problem is…

Slides:

Advertisements

Similar presentations

1. Online hiring cost calculation Recruitment function control Recruitment performance & hiring management analysis Recruitment function operations optimization.

Advertisements

Inventory Management & Administration System Tourism suite A powerful computer software application handling carefully your inventory department activity.

Data Mining Tools Overview Business Intelligence for Managers.

CONSUMER RESEARCH Chapter 2.

Accessing Organizational Information—Data Warehouse

Role of ICT in Business ICT in a business environment can be used for:

T T07-01 Sample Size Effect – Normal Distribution Purpose Allows the analyst to analyze the effect that sample size has on a sampling distribution.

Microarray Analysis Jesse Mecham CS 601R. Microarray Analysis It all comes down to Experimental Design Experimental Design Preprocessing Preprocessing.

Brenda Woods John Williams Daniel Bailey Breia Stamper.

Copyright © 2014 Pearson Education, Inc. 1 It's what you learn after you know it all that counts. John Wooden Key Terms and Review (Chapter 6) Enhancing.

What is R Muhammad Omer. What is R  R is the programing language software for statistical computing and data analysis  The R language is extensively.

© 2012 Ideal Analytics Limited. Banking. © 2012 Ideal Analytics Limited. 2 Banking – the gamut of all monetary transactions Banking these days engages.

Basic Marketing Research Customer Insights and Managerial Action

Chapter 12 Information Systems. Spreadsheets Databases 12-2.

2.3 Methods for Big Data What is “Big Data”? Summarizing Big Data.

Application of SAS®! Enterprise Miner™ in Credit Risk Analytics

What is R By: Wase Siddiqui. Introduction R is a programming language which is used for statistical computing and graphics. “R is a language and environment.

Lecture 7: Simulations.

Business Intelligence. business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data.

CIS 9002 Kannan Mohan Department of CIS Zicklin School of Business, Baruch College.

‘Big Data’ Panel Discussion Using data in applications Digital Ship Hamburg 2015.

Innovations in Justice Information Sharing Strategies and Best Practices November 30, 2006 Lisa M. Palmieri, CCA-Supervisory Intelligence Analyst President,

5-1 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

ALGORITHM CHAPTER 8. Chapter Outlines and Objectives  Define an algorithm and relate it to problem solving.  Define three construct and describe their.

SIMO SIMulation and Optimization ”New generation forest planning system” Antti Mäkinen Dept. of Forest Resource Management / University of Helsinki.

Integrating Upward Supporting managers and executives.

1 Topics about Data Warehouses What is a data warehouse? How does a data warehouse differ from a transaction processing database? What are the characteristics.

Who wants to be a Data Scientist? July 22, 2015 Jennifer Lewis Priestley, Ph.D. Professor of Statistics and Data Science.

1 Categories of data Operational and very short-term decision making data Current, short-term decision making, related to financial transactions, detailed.

+ Big Data IST210 Class Lecture. + Big Data Summary by EMC Corporation ( More videos that.

Innovation Work Circle: Big Data Presented By: Innovation Work Circle Group.

An Introduction to R Statistical Computing AMS 597 Stony Brook University Spring 2009 By Tianyi Zhang.

Economic, Social and Environmental Benefits Better Planning and Operational Decisions in Water Management Decision Making Capacity and Institutions; Stakeholder.

Introduction to R Carol Bult The Jackson Laboratory Functional Genomics (BMB550) Spring 2011.

1 1 Slide Simulation Professor Ahmadi. 2 2 Slide Simulation Chapter Outline n Computer Simulation n Simulation Modeling n Random Variables and Pseudo-Random.

 Data Sets too Large & Complex for Companies to Manage Within Traditional IT Systems  3 “Vs” › Volume › Velocity › Variety  Opportunity.

Data Resource Management Agenda What types of data are stored by organizations? How are different types of data stored? What are the potential problems.

What’s the Big Deal about Big Data? Jennifer Lewis Priestley, Ph.D. Professor of Statistics and Data Science.

Data Visualization Data visualization is the presentation of data in a pictorial or graphical format. For centuries, people have depended on visual representations.

Data Mining Concepts and Techniques Course Presentation by Ali A. Ali Department of Information Technology Institute of Graduate Studies and Research Alexandria.

R Roger Barlow HEP Computing seminar 21 st February 2008.

What’s the Big Deal about Big Data? 52 nd Annual ACMSE Conference Jennifer Lewis Priestley, Ph.D. Professor of Statistics and Data Science.

Copyright © 2016 Pearson Education, Inc. Modern Database Management 12 th Edition Jeff Hoffer, Ramesh Venkataraman, Heikki Topi CHAPTER 11: BIG DATA AND.

BIG DATA. The information and the ability to store, analyze, and predict based on that information that is delivering a competitive advantage.

© David L. Wells Integrating Analytics into Business Intelligence Dave Wells

Data Science Interview Questions 1.What do you mean by word Data Science? Data Science is the extraction of knowledge from large.

Leverage Big Data With Hadoop Analytics Presentation by Ravi Namboori Visit

Viewing Data-Driven Success Through a Capability Lens

1-1 Logic and Syntax A computer program is a solution to a problem.

Data Warehouse.

Marketing Decision-Making and Marketing Decisions

Emerging Trends in Information Technology

Chapter Ten Managing a Database.

Introduction to Geospatial Technologies in Ag

Big Data - og affald Helle Rootzen

Unit 9 – Spreadsheet Development

This presentation uses a free template provided by FPPT.com Computer Name: Ojen Shrestha Class: XI Section: G 1 Date:

Brochure Design Services That Every Business Needs

Introduction Data Mining for Business Analytics.

Managing Business Processes

QA Validation in Big Data

Big Data Young Lee BUS 550.

Dep. of Information Technology By: Raz Dara Mohammad Amin

Big Data: Four Vs Salhuldin Alqarghuli.

Programming For Big Data

Big data and Analytics for non-financial information

What Are Performance Counters?

Introduction to Programming

Presentation transcript:

Analytics vs Statistics the problem is… Bob McQuaid Decision Sciences Institute Meeting November 21, 2016

Scientist or Analyst?

Which is the egg? Statistics Analytics

Big Data: If just one of these? Volume – is lots of columns and rows of text/numeric data “Big” Variety – if lots of different kinds of data; think of all the data in a “house” at one point in time Velocity – is monitoring one stock price every 2 seconds “big” Veracity – if inspection is not 100% accurate, can this ever be “known”? http://www.ibmbigdatahub.com/infographic/four-vs-big-data

Live vs Lots vs Big

Programming not Analyzing? FROM R-PROJECT.ORG: an effective data handling and storage facility, a suite of operators for calculations on arrays, in particular matrices, a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either on-screen or on hardcopy, and a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

Continuous vs Categorical?

Hypothesize or Datamine

Semantic Analysis or Number Crunch

Advertising Analytics What’s in a name? Predictive Analytics Marketing Analytics Customer Analytics Advertising Analytics

Limited “engaged” hours… BREADTH DEPTH