Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Data Warehouse 98

Data Warehouse Azure SQL ETL 98

How to Learn Machine Learning

APRIL 26, 2025

It’s not simply about the numbers, but how they can communicate the story behind the data to then model complex datasets into insights that stakeholders can act on. Data engineers will also deal with the matters of data architecture and design of databases concerning the basic problem of how is data stored, structured, and accessed.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

phData

NOVEMBER 13, 2023

Read more about the dbt Explorer: Explore your dbt projects dbt Semantic Layer: Relaunch The dbt Semantic Layer is an innovative approach to solving the common data consistency and trust challenges. Tableau (beta) Google Sheets (beta) Hex Klipfolio PowerMetrics Lightdash Mode Push.ai

Database 52

Database Business Intelligence Business Intelligence Data Silos 52

DagsHub

AUGUST 23, 2024

Data quality is crucial across various domains within an organization. For example, software engineers focus on operational accuracy and efficiency, while data scientists require clean data for training machine learning models. Without high-quality data, even the most advanced models can't deliver value.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Alation

JULY 12, 2022

Many things have driven the rise of the cloud data warehouse. The cloud can deliver myriad benefits to data teams, including agility, innovation, and security. More users can access, query, and learn from data, contributing to a greater body of knowledge for the organization. Build Out a Data Synchronization Process.

Cloud Data 52

Cloud Data Data Warehouse Database Machine Learning 52