Pickl AI

APRIL 21, 2025

Big Data technologies include Hadoop, Spark, and NoSQL databases. Exploring the Data (Exploratory Data Analysis – EDA) Digging into the cleaned data to understand its basic characteristics, find patterns, identify trends, and visualize relationships. Data Science extracts insights and builds predictive models from processed data.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Mlearning.ai

MAY 23, 2023

This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA). Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus. Familiarity with libraries like pandas, NumPy, and SQL for data handling is important.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JULY 20, 2023

Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA). They should also consider leveraging cloud platforms like AWS or Google Cloud for handling large-scale datasets and computing resources if needed.

Analytics 40

Analytics Analytics Big Data Big Data 40