Business Analytics Course

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Business Analytics Course by Mind Map: Business Analytics Course

1. Day 1 Competing with Analytics

1.1. Session 1 Introduction to Business Analytics

1.1.1. Overview of Business Analytics

1.1.2. General Welcome & Introduction

1.1.3. Analytical Problems and Decision Making

1.1.4. Analytical Tools and Techniques

1.2. Session 2 Segmentation

1.3. Session 3 Predictive Modelling

1.4. Session 4 Campaigns

1.4.1. Intro to Campaign systems

1.4.2. Optimization

1.4.3. Integrating Campaigns

1.5. Tasks

1.5.1. Analytical Landscape Map

1.5.2. Design a Campaign

1.5.3. Segmentation Module

1.5.4. Quotient Survey

1.5.5. Predictive Modelling Module

1.6. Notes

2. Day 2 Online and Cloud Analytics

2.1. Session 1 Online Analytics

2.1.1. The Emerging Data Economy

2.1.2. Open Web Data

2.1.3. Corporate & Commercial

2.1.4. Analytical Tools and Techniques

2.2. Session 2 Analytics in the Cloud

2.2.1. Find, Share and Collaborate

2.2.2. Web Analytics

2.2.3. SAS on Demand

2.3. Session 3 Location and Mobile Analytics

2.3.1. Linking Mapping with Segmentation

2.3.2. Mapping in the Cloud

2.3.3. SAS for Mobile

2.4. Session 4 Analytics for Web Campaigns

2.4.1. Optimization

2.4.2. Customer Profiling

2.5. Tasks

2.5.1. Open Data Practicum

2.5.2. Web Analytics Practicum

2.5.3. Geo Segmentation

2.5.4. SAS Tutorials

2.6. Notes

3. Day 4 Analytics at Work

3.1. Session 1 Competitive Data

3.1.1. Analytics as a strategy

3.1.2. Key Competitive Data

3.2. Session 2 Data Privacy

3.2.1. Overview of Data Privacy

3.2.2. Privacy and the internet

3.3. Session 3 90 Day Project

3.4. Session 4 Value of Business Analytics

3.4.1. Opportunity & Value in Analytics

3.4.2. Opportunity Sizing

3.5. Tasks

3.5.1. Regulatory

3.5.2. Competition Design

3.5.3. Wish List

3.5.4. Funding Analytics

3.6. Notes

4. Day 3 Visual & Unstructured

4.1. Session 1 Effective Visual Analytics

4.1.1. Introduction to Effective Visual

4.1.2. Analytical Charts & Infographics

4.1.3. SAS Visual Tools

4.1.4. Analytical Tools and Techniques

4.2. Session 2 Qualitative Data Analysis

4.2.1. Analytics for Unstructured data

4.2.2. Market Research and Survey Analytics

4.2.3. Legal Analytics

4.2.4. Visualising Unstructured

4.3. Session 3 Semantic Web Analysis

4.3.1. Semantic & Social Web Analysis

4.3.2. Big Data Analytics

4.4. Session 4 Communicating Analytics

4.4.1. Communicating & interpretation

4.4.2. 90 Day Project Breifing

4.5. Tasks

4.5.1. Periodic Table

4.5.2. Dashboard Evaluation

4.5.3. Word Cloud Visuals

4.5.4. Reading the Boards

4.5.5. Social monitoring

4.6. Notes