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.

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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.

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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.

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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.

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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.

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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

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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.

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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?

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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?

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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.

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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.

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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.

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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.

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Dataversity

APRIL 21, 2022

SaaS apps are data-intensive, generating and accessing massive volumes of data in real time. Because of that, most organizations build SaaS apps on data warehouses instead of HTAP databases. For one, since SaaS apps operate on larger volumes of data, data warehouses […].

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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.

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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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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Dataversity

MARCH 1, 2021

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […]. Each business often uses one or more data […].

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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?

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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.

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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 […].

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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.

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Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

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Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. Preserve information: Keep your raw data raw.

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Dataversity

MAY 6, 2022

An underlying architectural pattern is the leveraging of an open data lakehouse. That is no surprise – open data lakehouses can easily handle digital-era data types that traditional data warehouses were not designed for. Data warehouses are great at both analyzing and storing […].

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Smart Data Collective

OCTOBER 17, 2022

Pipeline, as it sounds, consists of several activities and tools that are used to move data from one system to another using the same method of data processing and storage. Data pipelines automatically fetch information from various disparate sources for further consolidation and transformation into high-performing data storage.

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Smart Data Collective

JULY 9, 2023

By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse.

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AWS Machine Learning Blog

FEBRUARY 14, 2024

In this post, we discuss how to use the comprehensive capabilities of Amazon Bedrock to perform complex business tasks and improve the customer experience by providing personalization using the data stored in a database like Amazon Redshift. The foundation model then generates more relevant and accurate information.

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Dataconomy

FEBRUARY 27, 2025

Hadoop has become synonymous with big data processing, transforming how organizations manage vast quantities of information. As businesses increasingly rely on data for decision-making, Hadoop’s open-source framework has emerged as a key player, offering a powerful solution for handling diverse and complex datasets.

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Tableau

MARCH 30, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. Azure SQL Database.

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