Features of NoSQL Databases and their Usage for Analytics | 5 Conceptual Questions and Answers | Concept Infographic Note

 

Topics discussed in the post the following questionnaire :

Q1) What are some predominant features of No-SQL databases ?

Q2) Why NoSQL is called "SQL with a No " with "No" as the preceding string on SQL ?

Q3) How do organisations leverage NoSQL data for their businesses ?

Q4) Where are NoSQL databases useful ?

Q5) What do you mean by the statement , "The constraints of a relational database are relaxed ? "

Difference between RDBMS and NoSQL databases | 10 Conceptual Questions and Answers | Concept Infographic Note

Questions and answers discussed in the post:

Q1) What are the different ways in which RDBMS databases differ from NOSQL databases?

Q2) What are the Applications Level feature supported by RDBMS and NoSQL Databases ?

Q3) What are the principles of RDBMS and NoSQL type databases ?

Q4) Explain about Availability aspect of RDBMS and NoSQL type databases ?

Q5) What is the data velocity supported over RDBMS and NoSQL databases ?

Q6) What do you mean by Latency . What happens if Latency is High ? And what happens if Latency is Low ?

Q7) What is the data volume supported over RDBMS and NoSQL databases ?

Q8) What are the data sources present over RDBMS and NoSQL databases ?

Q9) What are the different data types that are present over RDBMS and NoSQL ?

Q10) What are the different data accesses that are present over RDBMS and NoSQL ?

Q11) What are the different technologies that are supported over RDBMS and NoSQL ?

Q12) Write about the cost aspects of RDBMS and NoSQL

Examples of Using "JOIN" function on Python Data Structures | Sample Conceptual Questions with Answers with examples | Infographic Note

 

Example - 01 : Joining Numeric List Elements with char string

Example - 02 : Joining Tuples with character string

Example - 03 : Joining List elements with long string

Example - 04 : Joining Character List Elements with long string

Example - 05 : Joining Character List Elements with null string

Effective Lambda Expressions and Anonymous Functions in Python : Infographic Note on concept of Lambda expressions , its usage , examples and applications

 

Simulation of Bubble Sort Operation over a List in Python : An Infographic Note for Better Understanding of Iterative Bubble Sort Process

 

Performing Bubble Sort Operation over a List in Python | Infographic Note on procedure for doing Bubble Sort with Code and Examples

 

Infographic Note on Z-Score in Statistics and Machine Learning with it's usage scenario , calculation , implication and applications

 

Infographic Note on why Outliers are not deleted at the time of Data Processing or Data Analysis in Statistics

 

Infographic Note with questions and answers on the concepts of MinMaxScaler function , Standard Scaler Function , Normalisation , Standardisation in Statistical Analysis

 

Infographic Note on Correlation Analysis using corr() function over a Pandas dataframe in Python

 

Infographic Note on Correlation Analysis of numerical attributes of a Pandas Dataframe in Python

 

Infographic Note on Python Code Analysis of a Sample Outliers Detection function over a numerical attribute in a pandas dataframe

 

Infographic Note on Outliers Detection , finding Inter-Quartile ranges and Interpreting Box-Plot diagrams over Pandas Dataframe in Python

 

Infographic Note on steps to perform Count , filter , group and aggregate numerical values over a dataset using Numpy and Pandas in Python using Jupyter Notebook IDE

 

Infographic Note on steps to formulate and perform a Hypothesis Test using Numpy , Pandas and Scipy Libraries of Python

 

Infographic Note on Introduction to Machine Learning using PyTorch with sample questions and answers

 

An Infographic Note Steps to follow for Installation of Pytorch Software over Jupyter Notebook

 

Infographic Note on difference between Pytorch and Tensorflow with respect to their features and provisions

 

Infographic Note on Numpy Arrays in Python with Questions and Answers on procedure to handle random numbers in an Array or Matrix Data Structure

 

Discussed the following questions in the above post :

Q1)If a programmer does not know the last number or position , then how can a programmer show the last position element of an array in Numpy ?

Q2) Using Slicing mechanism , retrieve the first two elements of the numpy array ?

Q3) Using Slicing mechanism , retrieve the last two elements of the numpy array ?

Infographic Note on Numpy Arrays in Python with Questions and Answers on Random Numeric Data Creation and Data Retrieval upon positional indexes

 

Discussed the following questions in the above post :

Q1) Give an example of SEED function and how to use it .

Q2) What is One-Dimensional indexing ?

Q3) Print first , last position elements of a Numpy Array

Q4) Print seond , third position elements of a Numpy Array

Q5) How to identify last number of numpy array ?