KDnuggets

JUNE 19, 2025

Python works best for: Exploratory data analysis and prototyping Machine learning model development Complex ETL with business logic Statistical analysis and research Data visualization and reporting Go: Built for Scale and Speed Go takes a different approach to data processing, focusing on performance and reliability from the start.

Python 165

Python Natural Language Processing Data Science Machine Learning 165

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Data Lakes 145

ODSC - Open Data Science

FEBRUARY 24, 2023

There are also plenty of data visualization libraries available that can handle exploration like Plotly, matplotlib, D3, Apache ECharts, Bokeh, etc. In this article, we’re going to cover 11 data exploration tools that are specifically designed for exploration and analysis. Output is a fully self-contained HTML application.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Pickl AI

SEPTEMBER 5, 2024

Storage Solutions: Secure and scalable storage options like Azure Blob Storage and Azure Data Lake Storage. Key features and benefits of Azure for Data Science include: Scalability: Easily scale resources up or down based on demand, ideal for handling large datasets and complex computations.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

The MLOps Blog

OCTOBER 20, 2023

And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. When data science was sexy , notebooks weren’t a thing yet.

SQL 52

SQL Database Data Scientist Python 52