Data Science Blog

MAY 20, 2024

It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL.

Data Pipeline 262

Data Pipeline Data Warehouse Azure Data Lakes 262

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Data Science Dojo

JULY 6, 2023

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. It allows data engineers to define and manage complex workflows as directed acyclic graphs (DAGs).

Data Engineering 195

Data Engineering Data Engineer Data Engineering Data Engineering 195

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

phData

SEPTEMBER 26, 2023

Sources The sources involved could influence or determine the options available for the data ingestion tool(s). These could include other databases, data lakes, SaaS applications (e.g. Data flows from the current data platform to the destination. The necessary access is granted so data flows without issue.

SQL 52

SQL Database ETL Data Modeling 52

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. Data Warehousing concepts and knowledge should be strong.

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52