## 01: Q01 – Q07 General Big Data, Data Science & Data Analytics Interview Q&As

Q01. How is Big Data used in industries?
A01. The main goal for most organisations is to enhance customer experience, and consequently increase sales. The other goals include cost reduction, better targeted marketing, fraud detection, identifying data breaches to enhance security, making existing processes more efficient, medical records to drug discovery and genetic disease exploration, and the list goes on.… Read more ...

## 02: Cleansing & pre-processing data in BigData & machine learning with Spark interview questions & answers

Q1. Why are data cleansing & pre-processing important in analytics & machine learning?
A1. Garbage in gets you garbage out. No matter how good your machine learning algorithm is.

Q2. What are the general steps of cleansing data
A2. General steps involve Deduplication, dropping/imputing missing values, fixing structural errors, removing the outliers, encoding the categorical values and scaling down the features.… Read more ...

## 03: Simple Linear Regression interview Q&As

Q01. What is a gradient? A01. In algebra we can represent a straight line with: y = mx + c A parabola is represented as: y = m1x2 + m2x + c, and so on. The diagram depicts the parabola y = x2.… Read more ...

## 04: Residuals, Cost/Loss functions, R-squared & Gradient Descent interview Q&As

Q01. What do you understand by the terms mean, variance, and standard deviation of the sample Vs. the population? A01. Given that the following are the number of job applications sent by 6 individuals:

Where X is the Sample.… Read more ...

## 05: Linear regression outputs, null hypothesis, t-test & p-value interview Q&As

Q1. How do you produce & interpret Linear Regression output? A1. Scatter plots can only detect obvious relationships between variables by looking at the graph, but we can use statistics to comment about the variable relationships as outlined below. The link 11A: Databricks – Spark ML – Pandas Dataframe &…

## What do data analysts, engineers & scientists do?

Today’s world run on data and no organisation would survive without data-driven decision making and strategic planning. There are several roles in the industry today like data analysts, data engineers, data scientists & business analysts that deal with data. Some of the skills required overlap among these roles.… Read more ...

Don't be overwhelmed by the number of Q&As & tech stacks as nobody knows everything, and often key Q&As at the right moment makes a difference.

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