Data Science Dojo

JULY 12, 2023

Welcome to the world of databases, where the choice between SQL (Structured Query Language) and NoSQL (Not Only SQL) databases can be a significant decision. In this blog, we’ll explore the defining traits, benefits, use cases, and key factors to consider when choosing between SQL and NoSQL databases.

SQL 195

SQL Database Big Data Big Data 195

Data Science Dojo

OCTOBER 31, 2024

Their role is crucial in understanding the underlying data structures and how to leverage them for insights. Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Programming Questions Data science roles typically require knowledge of Python, SQL, R, or Hadoop.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Data Science Dojo

JULY 6, 2023

It integrates seamlessly with other AWS services and supports various data integration and transformation workflows. Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

Smart Data Collective

MAY 29, 2023

Skills Sets to Look For When entering into the hiring process for a data analyst there are a few skills that are recommended to look for when narrowing down the pool of options. Data modeling will result in how, in part, a business will set standards.

Data Analyst 104

Data Analyst SQL Data Scientist Data Analysis 104

Smart Data Collective

JUNE 16, 2022

There are a lot of important queries that you need to run as a data scientist. This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. Types: HOLAP stands for Hybrid Online Analytical Processing.

Analytics 139

Analytics Analytics Data Scientist Data Warehouse 139

Pickl AI

APRIL 6, 2023

Understand the fundamentals of data engineering: To become an Azure Data Engineer, you must first understand the concepts and principles of data engineering. Knowledge of data modeling, warehousing, integration, pipelines, and transformation is required. Hands-on experience working with SQLDW and SQL-DB.

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

IBM Journey to AI blog

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70