Analytics Vidhya

OCTOBER 4, 2021

This article was published as a part of the Data Science Blogathon Image 1 What is data mining? Data mining is the process of finding interesting patterns and knowledge from large amounts of data. This analysis […].

Data Mining 324

Data Mining Data Mining Data Mining Data Warehouse 324

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

Pickl AI

APRIL 22, 2025

Summary: The snowflake schema in data warehouse organizes data into normalized, hierarchical dimension tables to reduce redundancy and enhance integrity. This approach is particularly valuable for organizations aiming to manage highly structured, multi-level data with minimal redundancy and greater consistency.

Data Warehouse 52

Data Warehouse Data Models Data Modeling Analytics 52

Dataversity

MARCH 21, 2022

While data lakes and data warehouses are both important Data Management tools, they serve very different purposes. If you’re trying to determine whether you need a data lake, a data warehouse, or possibly even both, you’ll want to understand the functionality of each tool and their differences.

Data Lakes 98

Data Lakes Data Warehouse Data Governance Data Quality 98

Dataversity

DECEMBER 18, 2023

To enable effective management, governance, and utilization of data and analytics, an increasing number of enterprises today are looking at deploying the data catalog, semantic layer, and data warehouse.

Data Warehouse 119

Data Warehouse Analytics Analytics 119

Data Science Dojo

MARCH 27, 2025

Thats where data normalization comes in. Its a structured process that organizes data to reduce redundancy and improve efficiency. Whether you’re working with relational databases, data warehouses , or machine learning pipelines, normalization helps maintain clean, accurate, and optimized datasets.

Database 195

Database Data Warehouse Machine Learning Machine Learning 195

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. We discussed the importance of aligning these systems strategically to balance their unique strengths while avoiding unnecessary complexity.

Data Warehouse 52

Data Warehouse Database Analytics Analytics 52

Dataversity

SEPTEMBER 24, 2021

We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 The reason is pretty obvious – businesses want to leverage the power of data […].

Data Warehouse 97

Data Warehouse Data Quality Data Governance Cloud Data 97

FlowingData

FEBRUARY 16, 2023

regulators and members of Congress are scrutinizing the deal, including by examining its potential to erode privacy: Kroger has carefully grown two “alternative profit business” units that monetize customer information, expected by Kroger to yield more than $1 billion in “profits opportunity.”

Data Warehouse 121

Data Warehouse 121

Dataconomy

JUNE 13, 2025

Data virtualization is transforming the way organizations access and manage their data. By allowing seamless integration of information from various sources without physical data movement, businesses can gain better insights and streamline their operations. What is data virtualization?

Data Visualization 91

Data Visualization Cloud Data Data Lakes Data Warehouse 91

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

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 331

Analytics Analytics AI AI 331

Dataconomy

MARCH 29, 2025

You need to provide the user with information within a short time frame without compromising the user experience. He cited delivery time prediction as an example, where each user’s data is unique and depends on numerous factors, precluding pre-caching. Data management is another critical area.

Data Warehouse 103

Data Warehouse AI AI Data Preparation 103

Data Science Dojo

SEPTEMBER 11, 2024

These experiences facilitate professionals from ingesting data from different sources into a unified environment and pipelining the ingestion, transformation, and processing of data to developing predictive models and analyzing the data by visualization in interactive BI reports.

Power BI 337

Power BI Data Pipeline Data Warehouse Data Engineering 337

Dataconomy

JUNE 3, 2025

A conformed dimension is a set of attributes that are shared across multiple fact tables within a data warehouse. This ensures that different business processes can utilize the same dimensional data, enabling a consistent understanding and analysis of information, regardless of the source.

ETL 91

ETL Data Warehouse Data Silos Data Lakes 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

MARCH 6, 2025

Data vault is not just a method; its an innovative approach to data modeling and integration tailored for modern data warehouses. As businesses continue to evolve, the complexity of managing data efficiently has grown. As businesses continue to evolve, the complexity of managing data efficiently has grown.

Data Warehouse 91

Data Warehouse Data Quality Data Models Data Modeling 91

Dataconomy

JUNE 10, 2025

By providing a structured way to analyze historical data, these databases empower organizations to uncover trends and patterns that inform strategies and optimize operations. Businesses can leverage analytics databases to enhance reporting, improve business intelligence (BI), and efficiently manage vast quantities of information.

Database 91

Database Analytics Analytics Business Intelligence 91

Data Science Dojo

SEPTEMBER 6, 2023

M aintaining the security and governance of data within a data warehouse is of utmost importance. Data Security: A Multi-layered Approach In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information.

Data Warehouse 195

Data Warehouse Data Governance Data Quality ETL 195

Flipboard

JULY 13, 2023

Hello, data enthusiast! In this article let’s discuss “Data Modelling” right from the traditional and classical ways and aligning to today’s digital …

Data Warehouse 123

Data Warehouse Data Models Data Modeling Big Data 123

Data Science Dojo

APRIL 25, 2023

Here are some essential SQL concepts that every data scientist should know: First, understanding the syntax of SQL statements is essential in order to retrieve, modify or delete information from databases. 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

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

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

Flipboard

MAY 12, 2023

Understand how data works at large companiesContinue reading on Towards Data Science »

Data Warehouse 132

Data Warehouse Data Science Big Data Big Data 132

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

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

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 108

Machine Learning Machine Learning ML ML 108

phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. Understanding the Basics What is a Data Warehouse?

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

databricks

JUNE 11, 2025

Just provide a high-level description of the agent’s task and connect your enterprise data — Agent Bricks handles the rest. Agent Bricks is optimized for common industry use cases, including structured information extraction, reliable knowledge assistance, custom text transformation, and building multi-agent systems.

AI 187

AI AI SQL Data Science 187

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. It’s also possible to employ extra caching or materialized views in the data warehouse in addition to caching in Looker (depending on the capability of your data warehouse). Final word.

Data Warehouse 126

Data Warehouse Database SQL Data Analyst 126

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 Big Data 112

Analytics Vidhya

APRIL 3, 2023

Introduction Companies can access a large pool of data in the modern business environment, and using this data in real-time may produce insightful results that can spur corporate success. Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers.

Data Engineering 319

Data Engineering Data Engineering Data Engineering Data Engineer 319

Flipboard

JUNE 5, 2023

Snowflake got its start by bringing data warehouse technology to the cloud, but now in 2023, like every other vendor, it finds artificial intelligence (AI) permeating nearly every discussion. In an exclusive interview with VentureBeat, Sunny Bedi, CIO and CDO at Snowflake, detailed the latest …

Data Warehouse 132

Data Warehouse Artificial Intelligence Artificial Intelligence AI 132

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

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 Engineering 306

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. By obtaining contextually relevant information, LLMs can produce more accurate and informative responses.

Data Warehouse 91

Data Warehouse Database Analytics Analytics 91