ODSC - Open Data Science

JANUARY 18, 2024

Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. Believe it or not, these skills are valuable in data engineering for data wrangling, model deployment, and understanding data pipelines. Stay on top of data engineering trends.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst SQL 52

ODSC - Open Data Science

APRIL 6, 2023

Data integration tools allow for the combining of data from multiple sources. These are used to extract, transform, and load (ETL) data between different systems. These services often provide integration with other cloud services, such as data storage and processing tools, to create end-to-end data workflows.

SQL 98

SQL Data Scientist Database Data Analysis 98

The MLOps Blog

OCTOBER 20, 2023

Example template for an exploratory notebook | Source: Author How to organize code in Jupyter notebook For exploratory tasks, the code to produce SQL queries, pandas data wrangling, or create plots is not important for readers. You can check the different Markdown syntax options in Markdown Cells — Jupyter Notebook 6.5.2 documentation.

SQL 52

SQL Database Data Scientist Python 52