DATA VISUALIZATION:
Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns.
WHY IS DATA VISUALIZATION IMPORTANT?
Using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports because human brain perceives, understands and grasps visuals better and faster than numbers or alphabets. Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments. Data visualization can:
• Identify areas that need attention or improvement.
• Clarify which factors influence customer behavior.
• Help you understand which products to place where.
• Predict sales volumes.
CASE STUDY IN Python:
The objective of this dashboard is to understand sales trends for one of the leading pharmaceutical company.
The client would like to come see a dynamic dashboard with different KPI's at different levels (National, Region & Territory etc). Create the below charts as these would help us explore the past data in a better manner and give a good picture of the progress and failures. This in turn would catalyse the decision-making process, making it easier, simpler and accurate.
ABOUT DATA:
The data attached is a two-year sales data of a pharma company which talks about sales in 2015 and 2016 across various regions and time frames.
Account Id : Customer ID
Account Name : Customer Name
Tier : Customer Segment
Sales 2015 : Sales for the year 2015
Sales 2016 : Sales for the year 2015
Units 2015 : No of Units sold for 2015
Units 2016 : No of Units sold for 2016