Big data Analytics for Retail Management using Tableau 2 x 12 days 24 Hrs Rs. 25,000
Step By Step Ways to Create Big Data Analytics. You Can Easily Analyze Data To Create Powerful Reports And Dashboards With Tableau. Our Course Is Meant For Professional Working At Different Levels Of Careers From Managers, Executive, Employees And Entrepreneur To Professionals Students
a) – Course Contents:
1 – Introduction to Tableau
2 – Connection to Data source.
3 – Table joining.
4 – Understand Tableau terminology.
5 – Tableau interface/Colors, Sessions etc…
6 – Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math and quick table calculations.
b) – Type of Charts:
1 – Cross Tabs
2 – Pie and bar charts
3 – Geographic maps
4 – Dual axis and combo charts with different mark types
5 – Data Import Export.
6 – Highlight tables
7 – Tree maps
8 – Scatter plot
c) – Build advanced chart types and visualizations.
1 – Build complex calculations to manipulate your data.
2 – Data Stages for analysis.
3 – Techniques for guided analytics, interactive dashboard design, and visual best practices.
d) – Case Studies for Tableau Visualization
1 – Business planning
2 – Production Planning
3 – Sale Analysis
4 – Production Analysis
e) – Stages of data analysis:
1 – Transform stage
2 – Filter stage
3 – Aggregator stage
4 – Remove duplicates stage
5 – Join stage
6 – Lookup stage
7 – Copy stage
8 – Sort stage
9 – Containers
f) – Retail Management Introduction.
1 – Essential Retail Management System Hardware
2 – History of Retail Management System Technology
3 – Cloud-based Vs. On-Premise Retail Management System Software.
4 – Inventory System for Retail Management.
5 – Data Visualization techniques for Retail Management.
g) – Analytics Reporting & Dashboard.
1 – Assortment Planning
2 – Demand Forecasting.
3 – Dynamic Pricing & Optimization.
4 – Foot traffic analytics
5 – Fraud Detection & Prevention.
6 – Interactive retail dashboards.
7 – Mix and match metrics or reports
8 – Monitoring & Analyzing Loss Prevention Metrics.
9 – Root Cause Analysis.
10 – Store Sales
11 – Store Deliveries
12 – Stores Sales Revenue
13 – Occasion Sales
14 – Store Performance
15 – Customer Segmentation
16 – Orders Distribution
17 – Product Type Orders