Posts

Showing posts with the label demographic analytics

Featured Post

15 Python Tips : How to Write Code Effectively

Image
 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index ...

Business Vs Demographic Vs Product Analytics

Image
List of top analytics areas and their differences 1. Analytics in Business Advertising Analytics Brand Analytics Promotion Analytics Business-to-business marketing Analytics Social Media Analytics Tracking Studies 2. Demographic Analytics Consumer Analytics Concept Testing Data Mining Customer Satisfaction Study Analytics Demographic Analytics Employee Satisfaction Analysis Text Mining Ethnographic Analytics Media Testing Opinion Polling and Predictive Analytics Usage & Attitude Studies Segmentation Analytics Semiotic and Cultural Analysis 3. Product Analytics Packaging and Design Effectiveness Analytics New Product Development Pricing Studies Product Testing Scenario Planning  Also Read Top IT Skills You Need to Become Data Analyst