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Data Analysis vs. Data Visualization – More Than Just Pretty Charts

Pickl AI

Modeling & Algorithms: Applying statistical models (like regression, classification, clustering) or Machine Learning algorithms to identify deeper patterns, make predictions, or classify data points. Collect Data: Gather customer demographics, purchase history, website interaction logs, customer support tickets, and subscription status.

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[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

The following figure represents the life cycle of data science. It starts with gathering the business requirements and relevant data. Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Why is data cleaning crucial?

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Analysis: This step involves applying statistical and Machine Learning techniques to analyse the cleaned data and uncover patterns, trends, and relationships.