Q&A

Difference among between data Analysis, data Analytics and Data Science

Data Analytics	Data Analysis	Data Science
Super set Process of Data Analysis	Sub Set Process of Data Analytics	Set Process
Past and Present study and future e prediction	Past discovery
What will happen in future	What happened
Tools: Tableau, Zoho Analytics,Talend, Hadoop, Xplenty, Kafka,Python,R-Language, Cassandra, MongoDB, HPCC, Spark, Datawrapper, PowerBI etc.	Python, R, PowerBI, Tableau, Excel
Data analytics predicts ‘what will happen next or what is going to be next?’	Data analysis is actually studying past data to understand ‘what happened?’
All analysis and prediction. Data analytics life cycle consists of Business Case Evaluation, Data Identification, Data Acquisition & Filtering, Data Extraction, Data Validation & Cleansing, Data Aggregation & Representation, Data Analysis, Data Visualization, and Utilization of Analysis Results	DA involves Querying, wrangling, statistical modelling, analysis and visualization.	DS involves data sourcing, cleansing, modelling, result evaluation and result testing and deployment

Data Analytics and data Science

Data Science is a combination of multiple disciplines – Mathematics, Statistics, Computer Science, Information Science, Machine Learning, and Artificial Intelligence.

2. Difference between mutable and immutable objects in python

In Python, Built-in projects like int, float, bool, string, tuple are immutable.

In Python, Built-in projects like list, dict, set are mutable.