Dataconomy

MAY 26, 2025

Azure Data Studio has rapidly gained popularity among developers and database administrators for its user-friendly design and powerful features. As a versatile tool, it simplifies the management of both SQL Server and Azure SQL databases, offering a modern alternative to traditional database management solutions.

Azure 91

Azure Database Administration SQL Database 91

Data Science 101

NOVEMBER 7, 2019

Azure Synapse. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. R Support for Azure Machine Learning. Azure Quantum.

Data Science 106

Data Science Azure SQL Machine Learning 106

phData

NOVEMBER 8, 2024

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. FAQs What is a Data Lakehouse?

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

phData

MAY 25, 2023

In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform. One of the easiest ways for Snowflake to achieve this is to have analytics solutions query their data warehouse in real-time (also known as DirectQuery).

Power BI 84

Power BI Analytics Analytics Azure 84

Dataconomy

SEPTEMBER 4, 2023

Organizations must diligently manage access controls, encryption, and data protection to mitigate risks. For example, the 2019 Capital One breach exposed over 100 million customer records, highlighting the need for robust security measures. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

IBM Journey to AI blog

JANUARY 10, 2023

This allows data that exists in cloud object storage to be easily combined with existing data warehouse data without data movement. The advantage to NPS clients is that they can store infrequently used data in a cost-effective manner without having to move that data into a physical data warehouse table.

Data Warehouse 52

Data Warehouse Data Analysis Data Analysis SQL 52

Alation

FEBRUARY 8, 2022

In contrast to this common, centralized approach, a data mesh architecture calls for responsibilities to be distributed to the people closest to the data. The three technology planes of a self-service data mesh are: Plane 1: Data Infrastructure Plane. Examples include public cloud vendors like AWS, Azure, and GCP.

Data Governance 52

Data Governance Data Engineering Data Engineering Data Engineer 52