- Is SQL needed to be a data scientist? - Jul 25, 2019.
As long as there is ‘data’ in data scientist, Structured Query Language (or see-quel as we call it) will remain an important part of it. In this blog, let us explore data science and its relationship with SQL.
Data Science, Relational Databases, SQL
7 Steps to Mastering SQL for Data Science — 2019 Edition - May 17, 2019.
Follow these updated 7 steps to go from SQL data science newbie to practitioner in a hurry. We consider only the necessary concepts and skills, and provide quality resources for each.
7 Steps, Data Science, Database, Relational Databases, SQL
- How To Write Better SQL Queries: The Definitive Guide – Part 2 - Aug 24, 2017.
Most forget that SQL isn’t just about writing queries, which is just the first step down the road. Ensuring that queries are performant or that they fit the context that you’re working in is a whole other thing. This SQL tutorial will provide you with a small peek at some steps that you can go through to evaluate your query.
Pages: 1 2
Algorithms, Complexity, Databases, Relational Databases, SQL
- How To Write Better SQL Queries: The Definitive Guide – Part 1 - Aug 23, 2017.
Most forget that SQL isn’t just about writing queries, which is just the first step down the road. Ensuring that queries are performant or that they fit the context that you’re working in is a whole other thing. This SQL tutorial will provide you with a small peek at some steps that you can go through to evaluate your query.
Pages: 1 2
Databases, Relational Databases, SQL
- 7 Steps to Mastering SQL for Data Science - Jun 16, 2016.
Follow these 7 steps to go from SQL data science newbie to seasoned practitioner quickly. No nonsense, just the necessities.
Pages: 1 2
7 Steps, Data Science, Database, Relational Databases, SQL
- Poll Results: Data Types/Sources Analyzed - May 17, 2014.
Trends in data sources for data mining include: table data dominates, followed by time series and text; audio, JSON grows in popularity, while itemsets decline; 70% access DB engines, but only 20% access NoSQL stores; Hadoop, MongoDB used more for text; Europe is lagging in NoSQL usage.
Data types, Hadoop, NoSQL, Poll, Relational Databases
