TDWI Analytics Fundamentals. Course Outline. Module One: Concepts of Analytics

Similar documents
How Data Science is Changing the Way Companies Do Business Colin White

Business Insight and Big Data Maturity in 2014

DATA ANALYTICS WITH R, EXCEL & TABLEAU

Architecture Overview for Data Analytics Deployments

Copyright - Diyotta, Inc. - All Rights Reserved. Page 2

Data Analytics for Semiconductor Manufacturing The MathWorks, Inc. 1

Real-time Streaming Insight & Time Series Data Analytic For Smart Retail

Delivering Value with Big Data and Analytics. Fern Halper VP and Senior Research Director for Advanced Analytics TDWI November 30, 2016

Sunnie Chung. Cleveland State University

Building the In-Demand Skills for Analytics and Data Science Course Outline

St Louis CMG Boris Zibitsker, PhD

High Performance Data Management The Impact on Oil & Gas Integrated Operations

Big Data Management Best Practices for Data Lakes Philip Russom, Ph.D.

MANAGEMENT INFORMATION SYSTEMS COURSES Student Learning Outcomes 1

Design of Information Systems 1st Lecture

Deloitte School of Analytics. Demystifying Data Science: Leveraging this phenomenon to drive your organisation forward

KnowledgeENTERPRISE FAST TRACK YOUR ACCESS TO BIG DATA WITH ANGOSS ADVANCED ANALYTICS ON SPARK. Advanced Analytics on Spark BROCHURE

MapR Pentaho Business Solutions

Accelerating Your Big Data Analytics. Jeff Healey, Director Product Marketing, HPE Vertica

E-guide Hadoop Big Data Platforms Buyer s Guide part 1

BIG DATA PROCESSING A DEEP DIVE IN HADOOP/SPARK & AZURE SQL DW

Brian Macdonald Big Data & Analytics Specialist - Oracle

Simplifying Your Modern Data Architecture Footprint

Case of predictive maintenance by analysis of acoustic data in an industrial environment

DATABIO: ADVANCED VISUALISATION OF BIG DATA FOR AGRICULTURE

2016 INFORMS International The Analytics Tool Kit: A Case Study with JMP Pro

In-Memory Analytics: Get Faster, Better Insights from Big Data

Oracle Retail Data Model (ORDM) Overview

Emerging Business Applications of High Performance Analytics

ARCHITECTURES ADVANCED ANALYTICS & IOT. Presented by: Orion Gebremedhin. Marc Lobree. Director of Technology, Data & Analytics

5th Annual. Cloudera, Inc. All rights reserved.

IBM s Analytics Transformation

Is Machine Learning the future of the Business Intelligence?

Data Warehousing. and Data Mining. Gauravkumarsingh Gaharwar

TECHNOLOGY PLATFORM STRATEGY

Jason Virtue Business Intelligence Technical Professional

Leveraging Data Analytics for Customer Support Efficiency

SAP Lumira, version for the SAP Business One application Overview Presentation

Insight is 20/20: The Importance of Analytics

TDWI strives to provide course books that are contentrich and that serve as useful reference documents after a class has ended.

The Age of Intelligent Data Systems: An Introduction with Application Examples. Paulo Cortez (ALGORITMI R&D Centre, University of Minho)

Ensuring a Sustainable Architecture for Data Analytics

Data Analytics: Drill, Hit, Predict and Visualize. Presenter: Dr. J. Joshua Thomas MSc, PhD

Big Data The Big Story

PRODUCT UPDATES APJ PARTNER SUMMIT - BALI. February Software AG. All rights reserved. For internal use only

"Charting the Course... MOC A: Architecting Microsoft Azure Solutions. Course Summary

Guide to Modernize Your Enterprise Data Warehouse How to Migrate to a Hadoop-based Big Data Lake

INTERACTIVE E-SCIENCE CYBERINFRASTRUCTURE FOR WORKFLOW MANAGEMENT COUPLED WITH BIG DATA TECHNOLOGY

Intel Public Sector 3

TDWI strives to provide course books that are contentrich and that serve as useful reference documents after a class has ended.

Hybrid Data Management

SAP Predictive Analytics Suite

Predictive Analytics With Oracle Data Mining

Designing a Microsoft SharePoint 2010 Infrastructure

Responsive enterprise the future of the enterprise PERSPECTIVE

WorkloadWisdom Storage performance analytics for comprehensive workload insight

Evolution to Revolution: Big Data 2.0

Analytical Tools 1. Analytical Tools Jennifer Dilly Ferris State University November 20, 2011

SAP Big Data. Markus Tempel SAP Big Data and Cloud Analytics Services

Workflow-Processing and Verification for Safety- Critical Engineering: Conceptual Architecture Deliverable D6.1

Complex Event Processing: Power your middleware with StreamInsight. Mahesh Patel (Microsoft) Amit Bansal (PeoplewareIndia.com)

INTRODUCING BIRST INFOR S GO-FORWARD BUSINESS INTELLIGENCE SOLUTION

BIOINFORMATICS AND SYSTEM BIOLOGY (INTERNATIONAL PROGRAM)

Converting Big Data into Business Value with Analytics Colin White

Data Analytics Training Program using

ETL challenges on IOT projects. Pedro Martins Head of Implementation

IoT ENABLED INTELLIGENT FLEET MANAGEMENT. Kalman Tiboldi Chief Business Innovation Officer

Mid-Atlantic CIO Forum

New Technologies in Banking

: 20776A: Performing Big Data Engineering on Microsoft Cloud Services

Olin Business School Master of Science in Customer Analytics (MSCA) Curriculum Academic Year. List of Courses by Semester

20775: Performing Data Engineering on Microsoft HD Insight

Microsoft Azure Essentials

TECHNOLOGY PLATFORM STRATEGY

2016 Spring Lunch & Learn Business Intelligence

The Rise of Engineering-Driven Analytics

Modernizing Data Integration

engage Out Requirements for NGA employees to have immersive experiences with industry or academia

Azure IoT Suite. Secure device connectivity and management. Data ingestion and command + control. Rich dashboards and visualizations

Boston Azure Cloud User Group. a journey of a thousand miles begins with a single step

PORTFOLIO AND TECHNOLOGY DIRECTION ARMISTEAD SAPP & RANDY GUARD

The Evolution of Big Data

Implementing a Data Warehouse with Microsoft SQL Server

Azure PaaS and SaaS Microsoft s two approaches to building IoT solutions

Big Data Job Descriptions. Software Engineer - Algorithms

EMC IT Big Data Analytics Journey. Mahmoud Ghanem Sr. Systems Engineer

SAP Predictive Analysis

Empowering insight-driven health care organizations with self-service analytics

Bringing the Power of SAS to Hadoop Title

Edward O Donnell. The Digital Procurement Process

The IBM Reference Architecture for Healthcare and Life Sciences

Azure. Bruno Kovačić Axilis, Microsoft MVP

The Right Tool For The Job

IBM SPSS Modeler Personal

Starting with Oracle Data Science in the Cloud

9. Verification, Validation, Testing

10231 Designing a Microsoft SharePoint Infrastructure 2010

Marketing & CRM Trends Manuel Hinz & Dr. Markus Wuebben

Cisco Connected Asset Manager for IoT Intelligence

Transcription:

TDWI Analytics Fundamentals Module One: Concepts of Analytics Analytics Defined Data Analytics and Business Analytics o Variations of Purpose o Variations of Skills Why Analytics o Cause and Effect o Strategy and Analytics o Tactics and Analytics o Operations and Analytics o Systemic Analytics Analytics Processes o Problem Framing o Problem Modeling o Solution Modeling o Visualization and Presentation o Understanding and Action Analytics Foundations o Data Scope of Data Finding Data Observations and Populations Raw Data vs. Summary Data Data Preparation o Statistics Histograms Distribution and Deviation Correlation Regression o Visualization Visual Design Choosing Charts and Graphs o Business Impact Simulation Optimization Automation Module Two: The Analytics Environment Analytics Stakeholders o The Participants Business Stakeholders Analytic Modelers and Data Scientists IT and Data Organizations Analytic Culture o Values, Beliefs, and Competencies TDWI page 1 of 6

Numeracy Collaboration Conversation Decision Styles Analytics Organizations o Organization Models Self Service Shared Services Central Services Hybrid Organizations o Analytics and Governance Analytics Capabilities o Business Capabilities Planning Executing Adapting Innovating o Analysis Capabilities Evaluating Detecting Predicting Classifying Recommending Monitoring o Data Capabilities Measuring Searching and Acquiring Blending and Integrating Securing Provisioning o A Capability-Based Framework Discovery Analytics Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Module Three: Analytics Architecture The Big Picture Data Architecture o Data Sources and Types o Data Acquisition o Data Ingestion o Persistence o Data Management Topology o Data Quality and Utility o Data Usage / Information Delivery Process Architecture o Next Generation BI TDWI page 2 of 6

Extending BI o Basic Data Analysis Statistical Analysis Time-Series Analysis o Discovery and Prediction Data Mining Predictive Modeling Ensemble Modeling o Text and Language Analysis Natural Language Processing Text Mining o People and Behaviors Sentiment Analysis Behavioral Analytics o People and Social Media Social Network Analysis Social Media Analytics o Events and Data Streams Stream Processing Complex Event Processing o Smart Machines Machine Learning Cognitive Computing Technology Architecture o Connectivity SQL Messaging Services Replication Virtualization o Data Stores RDBMS Columnar MPP MDDB NoSQL In Memory o Data Analysis Data Mining Analytic Modeling Big Data Analytics Streaming Analytics Event Processing Machine Learning etc. o Data Flow Batch Real-time Streams o Management Workflow TDWI page 3 of 6

o Service Levels Platforms Servers Appliances Cloud Module Four: Analytic Modeling The Roles of Models o Understanding the Problem Space o Understanding the Data o Understanding the Language o Understanding the Business Dynamics Kinds of Models o Framing Models Questioning Kernel Seeking o Cause-Effect Models Influence Models Causal Loop Models o Data Models Physical Models Logical Models Conceptual Models o Language Models Ontology Taxonomy Lexicon Semantics o Solution Models Formula Based Algorithm Based Problem Modeling o Framing the Problem o Influence Diagramming o Causal Modeling Solution Modeling o Formula Based Modeling Structuring Defining Documenting Developing Parameterizing Visualizing o Algorithm Based Modeling Business Understanding Data Understanding Data Preparation Model Building Evaluation TDWI page 4 of 6

Deployment Module Five: Applied Analytics Discovery Analytics Experimental Design Rule Discovery Data Mining Regression Models Descriptive Analytics Statistical Models Probability Distribution Models Monte Carlo Models Diagnostic Analytics Control Charts Classification Models Abnormal Condition Models Predictive Analytics Regression Models Neural Network Models Time Series Forecasting Models Bayes Theorem Models Prescriptive Analytics Discrete Event Models Continuous Simulation Models Optimization Models Linear Programming Models Module Six: Summary and Conclusion TDWI page 5 of 6

Summary of Key Points References and Resources TDWI page 6 of 6