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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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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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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Hacker News

NOVEMBER 14, 2023

I recently blogged about why I believe the future of cloud data services is large-scale and multi-tenant, citing, among others, S3. “Top Serving customers over large resource pools provides unparalleled efficiency and reliability at scale.”

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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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Alation

JULY 28, 2022

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. Yet the cloud, according to Sacolick, doesn’t come cheap. “A Migrate What Matters.

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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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Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

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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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IBM Journey to AI blog

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

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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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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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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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IBM Journey to AI blog

MARCH 14, 2024

The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage. Also, traditional database management tasks, including backups, upgrades and routine maintenance drain valuable time and resources, hindering innovation.

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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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Data Science Dojo

FEBRUARY 1, 2023

Introduction Dedicated SQL pools offer fast and reliable data import and analysis, allowing businesses to access accurate insights while optimizing performance and reducing costs. DWUs (Data Warehouse Units) can customize resources and optimize performance and costs.

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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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AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

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Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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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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Data Science Connect

JANUARY 27, 2023

If you’re interested in becoming a data engineer, there are several key skills and technologies that you should familiarize yourself with. In this blog post, we will be discussing 7 tips that will help you become a successful data engineer and take your career to the next level.

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Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. option("multiLine", "true").option("header", option("header", "false").option("sep",

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Towards AI

APRIL 10, 2024

Create S3 Bucket In my previous blog, I explained the way to create S3 Bucket. Image by Author Configure PostgreSQL Database Step 1. Search for RDS Services, click on Create database, and select Standard create & move down. But how EC2 will communicate with this database? Let’s dive in! You can refer to it.

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AWS Machine Learning Blog

DECEMBER 16, 2024

Now they can access databases and data warehouses, as well as unstructured business data, like emails, reports, charts, graphs, and images. Access all your data whether its stored in data lakes, data warehouses, third-party or federated data sources. And now, it still is.

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Smart Data Collective

JUNE 6, 2021

Google BigQuery is a service (within the Google Cloud platform (GCP)) implemented to collect and analyze big data (also known as a data warehouse). If you’re looking for a cost-effective, diverse and easily usable data warehouse, Google BigQuery may be the way to go. What is Big Data?” References.

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IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

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Dataversity

NOVEMBER 6, 2024

As businesses grow, so does the complexity of managing and analyzing data. Traditionally, relational database management systems (RDBMS) have been the backbone of data storage, offering robust and reliable transactional capabilities.

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phData

NOVEMBER 4, 2024

Snowflake excels in efficient data storage and governance, while Dataiku provides the tooling to operationalize advanced analytics and machine learning models. Together they create a powerful, flexible, and scalable foundation for modern data applications.

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Pickl AI

JULY 14, 2024

Summary: This blog explores the different types of keys in DBMS, including Primary, Unique, Foreign, Composite, and Super Keys. It highlights their unique functionalities and applications, emphasising their roles in maintaining data integrity and facilitating efficient data retrieval in database design and management.

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phData

NOVEMBER 9, 2023

This blog was originally written by Keith Smith and updated for 2024 by Justin Delisi. Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. What Components Make up the Snowflake Data Cloud? What is a Cloud 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. Now you’re ready to connect to the EC2 instance using SSH. Open an SSH client.

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phData

NOVEMBER 8, 2024

Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms. In this blog, we will discuss: What is the Open Table format (OTF)? Delta Lake became popular for making data lakes more reliable and easy to manage.

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IBM Journey to AI blog

APRIL 8, 2024

The new Amazon Relational Database Service (Amazon RDS) for Db2 offering allows customers to migrate their existing, self-managed Db2 databases to the cloud and accelerate strategic modernization initiatives. Can Amazon RDS for Db2 be used for running data warehousing workloads?

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IBM Journey to AI blog

SEPTEMBER 11, 2023

Thus, was born a single database and the relational model for transactions and business intelligence. Its early success, coupled with IBM WebSphere in the 1990s, put it in the spotlight as the database system for several Olympic games, including 1992 Barcelona, 1996 Atlanta, and the 1998 Winter Olympics in Nagano.

Database 101

Database SQL Data Warehouse Machine Learning 101

Dataversity

DECEMBER 12, 2022

Here in the early stages of this “stream revolution,” developers are building modern analytics applications that use continuously delivered real-time data. The post Is Your Database Built for Streaming Data? Yet while streams are clearly the […]. appeared first on DATAVERSITY.

Database 52

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Dataversity

MAY 2, 2022

If you’re building an analytics application for customers, then you’re probably wondering: What’s the right database backend? Your natural instinct might be to use what you know, like PostgreSQL or MySQL or even extend a data warehouse beyond its core BI dashboards and reports. But analytics for external […].

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