ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. These tools will help make your initial data exploration process easy. You can watch it on demand here.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Pickl AI

APRIL 21, 2025

This crucial step involves handling missing values, correcting errors (addressing Veracity issues from Big Data), transforming data into a usable format, and structuring it for analysis. This often takes up a significant chunk of a data scientist’s time. Think graphs, charts, and summary statistics.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Mlearning.ai

JULY 11, 2023

This includes important stages such as feature engineering, model development, data pipeline construction, and data deployment. For instance, feature engineering and exploratory data analysis (EDA) often require the use of visualization libraries like Matplotlib and Seaborn.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40