Data Science Dojo

MAY 10, 2023

In the context of data science, software engineers play a crucial role in creating robust and efficient software tools that facilitate data scientists’ work. They collaborate with data scientists to ensure that the software meets their needs and supports their data analysis and modeling tasks.

Data Science 368

Data Science Database Administration Data Scientist Machine Learning 368

ODSC - Open Data Science

APRIL 3, 2023

We looked at over 25,000 job descriptions, and these are the data analytics platforms, tools, and skills that employers are looking for in 2023. Excel is the second most sought-after tool in our chart as you’ll see below as it’s still an industry standard for data management and analytics.

Analytics 52

Analytics Analytics Data Analyst SQL 52

ODSC - Open Data Science

JANUARY 18, 2024

Like with any professional shift, it’s always good practice to take inventory of your existing data science strengths. Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. With that said, each skill may be used in a different manner.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

APRIL 6, 2023

You can perform data analysis within SQL Though mentioned in the first example, let’s expand on this a bit more. SQL allows for some pretty hefty and easy ad-hoc data analysis for the data professional on the go. Data integration tools allow for the combining of data from multiple sources.

SQL 98

SQL Data Scientist Database Data Analysis 98

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. documentation.

SQL 52

SQL Database Data Scientist Python 52