Remove introduction-to-databases-in-data-science
article thumbnail

KDnuggets News, September 13: Getting Started with SQL in 5 Steps • Introduction to Databases in Data Science

KDnuggets

Getting Started with SQL in 5 Steps • Introduction to Databases in Data Science • Time 100 AI: The Most Influential?

article thumbnail

Introduction to Databases in Data Science

KDnuggets

Understand the relevance of databases in data science. Also learn the fundamentals of relational databases, NoSQL database categories, and more.

Database 108
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How to Normalize Relational Databases With SQL Code?

Analytics Vidhya

Introduction Data is the new oil in this century. The database is the major element of a data science project. To generate actionable insights, the database must be centralized and organized efficiently. So, we are […] The post How to Normalize Relational Databases With SQL Code?

article thumbnail

Step-by-Step Roadmap to Learn SQL in 2023

Analytics Vidhya

Introduction Structured Query Language is a powerful language to manage and manipulate data stored in databases. SQL is widely used in the field of data science and is considered an essential skill to have if you work with data.

SQL 223
article thumbnail

Reconciling The Data In Your Databases With Datafold

Data Engineering Podcast

Summary A significant portion of data workflows involve storing and processing information in database engines. In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Data lakes are notoriously complex.

Database 147
article thumbnail

Find Out About The Technology Behind The Latest PFAD In Analytical Database Development

Data Engineering Podcast

Summary Building a database engine requires a substantial amount of engineering effort and time investment. In this episode he explains how he used the combination of Apache Arrow, Flight, Datafusion, and Parquet to lay the foundation of the newest version of his time-series database. Data lakes are notoriously complex.

Database 162
article thumbnail

Reflecting On The Past 6 Years Of Data Engineering

Data Engineering Podcast

In that time there have been a number of generational shifts in how data engineering is done. Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Summary This podcast started almost exactly six years ago, and the technology landscape was much different than it is now.