databricks

JUNE 11, 2025

Published: June 11, 2025 Announcements 5 min read by Ali Ghodsi , Stas Kelvich , Heikki Linnakangas , Nikita Shamgunov , Arsalan Tavakoli-Shiraji , Patrick Wendell , Reynold Xin and Matei Zaharia Share this post Keep up with us Subscribe Summary Operational databases were not designed for today’s AI-driven applications.

Database 204

Database Data Lakes ETL Analytics 204

Pickl AI

DECEMBER 15, 2024

Summary : This guide provides an in-depth look at the top data warehouse interview questions and answers essential for candidates in 2025. Covering key concepts, techniques, and best practices, it equips you with the knowledge needed to excel in interviews and demonstrates your expertise in data warehousing.

Data Warehouse 52

Data Warehouse ETL Database Data Quality 52

Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

Data Lakes 135

Data Lakes Data Warehouse Big Data Big Data 135

Dataconomy

OCTOBER 17, 2023

Want to create a robust data warehouse architecture for your business? The sheer volume of data that companies are now gathering is incredible, and understanding how best to store and use this information to extract top performance can be incredibly overwhelming.

Data Warehouse 103

Data Warehouse Big Data Big Data ETL 103

Precisely

JANUARY 9, 2025

The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning. In the beginning, there was a data warehouse The data warehouse (DW) was an approach to data architecture and structured data management that really hit its stride in the early 1990s.

Data Warehouse 119

Data Warehouse Hadoop Data Lakes Data Governance 119

Data Science Dojo

APRIL 25, 2023

It is a programming language used to manipulate data stored in relational databases. Mastering SQL concepts allows a data scientist to quickly analyze large amounts of data and make decisions based on their findings. A good knowledge of these commands can help a data scientist perform complex operations with ease.

Data Scientist 370

Data Scientist SQL Machine Learning Machine Learning 370

Dataversity

FEBRUARY 5, 2025

In the first part of this series, we explored how harmonizing relational database management systems (RDBMS) with data warehouses (DWH) can drive scalability, efficiency, and advanced analytics.

Data Warehouse 52

Data Warehouse Database Analytics Analytics 52

Dataconomy

MARCH 20, 2025

What is a data mart? A data mart is a specialized segment of a data warehouse tailored for specific business units, enhancing data accessibility and analysis. Consolidated views: They provide a unified perspective of data, facilitating better decision-making across various business functions.

Data Warehouse 91

Data Warehouse ETL Data Quality Database 91

Dataconomy

MAY 27, 2024

In the six years since, solutions to the centralized data problem have emerged, many of them employing cutting-edge web3 technologies like blockchain, zero-knowledge proofs (ZKPs), and self-sovereign identities (SSIs) to put users back in the data driver’s seat. In the past two years alone, 2.6

Data Warehouse 213

Data Warehouse Database SQL Analytics 213

Dataconomy

APRIL 27, 2023

What is an online transaction processing database (OLTP)? OLTP is the backbone of modern data processing, a critical component in managing large volumes of transactions quickly and efficiently. Initially, the OLTP concept was restricted to in-person exchanges that involved the transfer of goods, money, services, or information.

Database 159

Database Data Scientist Data Mining Data Mining 159

Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is a Database?

Data Warehouse 52

Data Warehouse Database Data Analysis Data Analysis 52

Smart Data Collective

FEBRUARY 20, 2022

Since databases store companies’ valuable digital assets and corporate secrets, they are on the receiving end of quite a few cyber-attack vectors these days. How can database activity monitoring (DAM) tools help avoid these threats? What are the ties between DAM and data loss prevention (DLP) systems? How do DAM solutions work?

Database 130

Database Machine Learning Machine Learning Data Warehouse 130

databricks

JUNE 11, 2025

Agent Bricks is optimized for common industry use cases, including structured information extraction, reliable knowledge assistance, custom text transformation, and orchestrated multi-agent systems. We auto-optimize over the knobs, gain confidence that you are on the most optimized settings.

Analytics 246

Analytics Analytics AI AI 246

AWS Machine Learning Blog

OCTOBER 28, 2024

The workflow includes the following steps: Within the SageMaker Canvas interface, the user composes a SQL query to run against the GCP BigQuery data warehouse. Athena returns the queried data from BigQuery to SageMaker Canvas, where you can use it for ML model training and development purposes within the no-code interface.

Machine Learning 111

Machine Learning Machine Learning ML ML 111

Smart Data Collective

APRIL 8, 2020

Furthermore, it has been estimated that by 2025, the cumulative data generated will triple to reach nearly 175 zettabytes. Demands from business decision makers for real-time data access is also seeing an unprecedented rise at present, in order to facilitate well-informed, educated business decisions.

Data Warehouse 144

Data Warehouse Big Data Big Data Big Data Analytics 144

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Flipboard

JANUARY 24, 2025

RAG data store The Retrieval Augmented Generation (RAG) data store delivers up-to-date, precise, and access-controlled knowledge from various data sources such as data warehouses, databases, and other software as a service (SaaS) applications through data connectors.

AWS 160

AWS AI AI Data Warehouse 160

Smart Data Collective

JUNE 15, 2021

How companies gather, manage and control data has undeniably become one of the most important aspects of business success today. This is precisely why many business owners turn to data platform solutions such as Looker in order to leverage their data faster using powerful databases. 3 – Aggregate your data.

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Data Warehouse Database SQL Data Analyst 126

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Smart Data Collective

MAY 16, 2022

Data management software helps in reducing the cost of maintaining the data by helping in the management and maintenance of the data stored in the database. It also helps in providing visibility to data and thus enables the users to make informed decisions. They are a part of the data management system.

Data Warehouse 136

Data Warehouse Data Mining Data Mining Data Mining 136

Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

Data Warehouse 52

Data Warehouse ETL Data Mining Data Mining 52

Pickl AI

FEBRUARY 3, 2025

Summary: A Data Warehouse consolidates enterprise-wide data for analytics, while a Data Mart focuses on department-specific needs. Data Warehouses offer comprehensive insights but require more resources, whereas Data Marts provide cost-effective, faster access to focused data.

Data Warehouse 52

Data Warehouse Analytics Analytics Database 52

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

IBM Journey to AI blog

APRIL 24, 2023

Why data warehousing is critical to a company’s success Data warehousing is the secure electronic information storage by a company or organization. Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions.

Data Warehouse 112

Data Warehouse Data Lakes Database Artificial Intelligence 112

Dataconomy

MAY 12, 2025

LlamaIndex serves as a robust data framework designed to optimize the use of large language models. It simplifies the connection between varied data sources and LLMs, facilitating seamless access to information. Data ingestion Data ingestion in LlamaIndex is made efficient through LlamaHub data connectors.

Data Warehouse 91

Data Warehouse Database Analytics Analytics 91

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. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Data Science in Practice

JANUARY 13, 2025

The blog post explains how the Internal Cloud Analytics team leveraged cloud resources like Code-Engine to improve, refine, and scale the data pipelines. Background One of the Analytics teams tasks is to load data from multiple sources and unify it into a data warehouse. Database size limits of 10GB.

ETL 100

ETL Data Pipeline Database Data Warehouse 100

Dataconomy

MAY 27, 2025

The contemporary business world is more information-driven than it has ever been. Businesses depend on timely information to make decisions, spot trends, and perform business in an efficient manner. For individuals who aspire to use data to drive positive change, an MIS degree is a solid foundation.

Analytics 91

Analytics Analytics Database Data Warehouse 91

Analytics Vidhya

MARCH 10, 2023

Introduction Snowflake is a cloud-based data warehousing platform that enables enterprises to manage vast and complicated information by providing scalable storage and processing capabilities. It is intended to be a fully managed, multi-cloud solution that does not need clients to handle hardware or software.

Analytics 306

Analytics Analytics Data Warehouse Data Engineer 306

Pickl AI

MARCH 24, 2025

Summary: Online Analytical Processing (OLAP) systems in Data Warehouse enable complex Data Analysis by organizing information into multidimensional structures. Key characteristics include fast query performance, interactive analysis, hierarchical data organization, and support for multiple users. What is OLAP?

Data Analysis 52

Data Analysis Data Analysis Database Analytics 52

Dataconomy

MARCH 26, 2025

ETL pipelines are revolutionizing the way organizations manage data by transforming raw information into valuable insights. They serve as the backbone of data-driven decision-making, allowing businesses to harness the power of their data through a structured process that includes extraction, transformation, and loading.

ETL 91

ETL Data Pipeline Business Intelligence Business Intelligence 91

Smart Data Collective

JUNE 6, 2021

In the simplest of terms, the latter refers to a system that examines large bodies of data with the goal of uncovering trends, patterns, correlations and other helpful information. What is big data used for? Customer experience is another key area that can benefit from big data analytics. Big data analytics advantages.

Big Data Analytics 137

Big Data Analytics Big Data Analytics Big Data Big Data 137

Dataversity

DECEMBER 15, 2021

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization. For example, most data warehouses […].

Data Warehouse 98

Data Warehouse Data Lakes Database Business Intelligence 98

Flipboard

JUNE 17, 2023

Our guest on the GeekWire Podcast is business and tech leader Bob Muglia, a startup investor and advisor who played a pivotal role in Microsoft’s database and server products, and was CEO of data warehouse company Snowflake Computing. We are putting ourselves into these systems.

AI 169

AI AI Data Warehouse Artificial Intelligence 169

Dataconomy

JUNE 4, 2025

Data ingestion is a crucial process in handling vast amounts of information that organizations generate and interact with daily. It encompasses various methods to collect, process, and utilize data. What is data ingestion? Overview of ETL ETL involves the specialized process of extracting, transforming, and loading data.

ETL 91

ETL Data Quality Data Warehouse Analytics 91

Flipboard

MAY 30, 2025

A generative AI foundation can provide primitives such as models, vector databases, and guardrails as a service and higher-level services for defining AI workflows, agents and multi-agents, tools, and also a catalog to encourage reuse. Considerations here are choice of vector database, optimizing indexing pipelines, and retrieval strategies.

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AWS AI AI Database 141