BIG DATA ANALYTICS WORKSHOPFOR MANAGERS Endorsed by

10 - 12 March, 2019

BIG DATA ANALYTICS WORKSHOPFOR MANAGERStopics include:

INTRODUCTION

VISION & STRATEGY

ARCHITECTURE & DATA

APPLICATION

DATA SCIENCE TOOLS

DATA EXTRACTION & INTERPRETATION

STATISTICS AND ARTIFICIAL INTELLIGENCE MODELS

DATA VISUALIZATION

DATA SCIENCE PROJECT MANAGEMENT

DATA DRIVEN DECISION MAKING

SHIFTING FROM MODELS TO PRACTICAL USE CASE

PROGRAM OVERVIEWThe Big Data Analy�cs Workshop for Managers offered by RIT Dubai is intended for senior managers from every diverse fields, who want to incorporate Big Data and employ Data Science tools in developing and imple-men�ng new strategies in their organiza�ons.

DAY 01

What is Big Data? What is Data Science?The importance of Big Data in management and leadership.Challenges and opportuni�es.The 5 ,3 and 10 Vs of Big Data.The main chapters of Data Science.Defining a strategy with Big Data: collabora�on vs compe��on.

WHY DO WE NEED BIG DATA AND WHAT WILL IT BRING TO OUR ORGANIZATION? WHAT KIND OFDATA DO WE NEED?

INTRODUCTION

VISION & STRATEGYAligning data and data science tools to the organiza�on’s needs.Introducing Big Data in the organiza�on. Technology, personnel and culture changes.Use of tradi�onal strategy tools when implemen�ng Big Data: Change Management Strategies, VMOST (vision, mission, objec�ves, strategy, tac�cal), SWOT (strengths, weaknesses, opportuni�es threats), PEST (poli�cal, economic, social technology), SOAR (strengths, opportuni�es, aspira�ons, results), Porter’s Five Forces (threat of new entrants, threat of subs�tutes, bargaining power of customers, bargaining power of suppliers, industry rivalry).

ARCHITECTURE & DATA

What kind of data is available?Quan�ta�ve and qualita�ve data. Structured data and unstructured data. Sta�c and streaming data.Architectures for Data Scien�sts. Data Base and Data Warehouse, Cloud Compu�ng.

APPLICATIONApplica�on domains for Big Data: Agriculture, business, consumer applica�on and smart home, educa�on, energy manage ment, engineering, environmental monitoring government, industry, Internet of Things (IoT), media, medical and health care, poli�cs, privacy, public safety, science, smart ci�es, etc.

3 Days Workshop

DAY 02WE HAVE THE DATA, WHAT CAN WE DO WITH IT? HOW DO WE GET THE INFORMATION WE NEED?

Data storage and managementData cleaningData miningData analysisData languagesData integra�on

DATA SCIENCE TOOLS

Methods for extrac�ng informa�on from the exis�ng dataDescrip�ve and inferen�al sta�s�cs, sta�s�cal testsInterpre�ng data, ethics, presen�ng and communica�ng results

DATA EXTRACTION & INTERPRETATION

Regression, �me series, sta�s�cal modeling and fi�ngData analysis and predic�ve analy�csMachine learning, ar�ficial intelligenceApplica�ons of ar�ficial intelligence in Machine vision Natural language processing Expert systems Gaming Self-teaching systems Intelligent robots

STATISTICS AND ARTIFICIAL INTELLIGENCE MODELS

DATA VISUALIZATIONData visual analysis and visualiza�on tools

DAY 03WHAT ARE SOME REAL-LIFE APPLICATIONS OF BIG DATA IN MANAGEMENT SCIENCE?

Important steps for making data-driven decisionsProject management

DATA SCIENCE PROJECT MANAGEMENT

Compe��ve advantage with data-driven decisions and avoiding data-driven disastersDecision analysis and mul�-criteria decision makingData visual analysis and visualiza�on tools

DATA DRIVEN DECISION MAKING

SHIFTING FROM MODELS TO PRACTICAL USE CASEOp�miza�on problems. Linear programmingNetwork models Transporta�on Transshipment Assignment and maximum flow problemsTransporta�onTransshipmentAssignment and maximum flow problemsApplica�ons of �me series and forecas�ngApplica�ons of Markov processes

DR. MIHAIL BARBOSUSUBJECT MATTER EXPERT

Director of the Data and Predic�ve Analy�cs Center – RIT New York

Dr. Mihail Barbosu completed his Ph.D. in France at Paris 6 University and Paris Observatory. He is Profes-sor in the School of Mathema�cal Sciences and Director of the Data and Predic�ve Analy�cs Center at RIT. Previously he was Head of the School of Mathema�cal Sciences at RIT and Chair of the Department of Mathema�cs at State University of New York at Brockport. Dr. Barbosu’s experience includes Mathema�-cal Modeling, Data and Predic�ve Analy�cs, Academic Management, Dynamical Systems and Space Dynamics.

PROGRESS IN YOURCAREER