Hacker News

DECEMBER 4, 2024

We are excited to release Crunchy Data Warehouse, a modern data warehouse for Postgres. Crunchy Data Warehouse combines Postgres with Iceberg, Parquet, and data lake formats for fast analytics queries and cost efficient storage.

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Dataconomy

APRIL 13, 2021

Data professionals have long debated the merits of the data lake versus the data warehouse.

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Analytics Vidhya

JANUARY 2, 2023

Introduction Delta Lake is an open-source storage layer that brings data lakes to the world of Apache Spark. Delta Lakes provides an ACID transaction–compliant and cloud–native platform on top of cloud object stores such as Amazon S3, Microsoft Azure Storage, and Google Cloud Storage.

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Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

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Data Lakes Analytics Analytics Data Warehouse 178

Analytics Vidhya

OCTOBER 10, 2022

Introduction Most of you would know the different approaches for building a data and analytics platform. You would have already worked on systems that used traditional warehouses or Hadoop-based data lakes. The post Warehouse, Lake or a Lakehouse – What’s Right for you?

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Data Science Blog

MAY 20, 2024

Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process. It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models.

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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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Analytics Vidhya

OCTOBER 10, 2022

Enterprises have slowly started adopting Lakehouses for their data ecosystems as they offer cost efficiencies of data lakes and the performance of warehouses. […]. The post Delta Lake in Action – Quick Hands-on Tutorial for Beginners appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 27, 2023

Delta Lake allows businesses to access and break new data down in real time. Delta Lake is an open-source warehouse layer designed to run on top of data lakes analogous to […] The post A Comprehensive Guide on Delta Lake appeared first on Analytics Vidhya.

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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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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. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

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KDnuggets

DECEMBER 14, 2021

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

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ODSC - Open Data Science

JUNE 22, 2023

While databases were the traditional way to store large amounts of data, a new storage method has developed that can store even more significant and varied amounts of data. These are called data lakes. What Are Data Lakes? In many cases, this could mean using multiple security programs and platforms.

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Smart Data Collective

MARCH 30, 2022

Azure Data Lake Storage Gen2 is based on Azure Blob storage and offers a suite of big data analytics features. If you don’t understand the concept, you might want to check out our previous article on the difference between data lakes and data warehouses. Determine your preparedness.

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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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Data Warehouse Data Lakes Azure AWS 147

Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The term and its underlying technology have been thriving more than ever.

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Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?

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Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

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Analytics Analytics Big Data Analytics Big Data Analytics 203

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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Dataversity

OCTOBER 11, 2021

The post Data Lakes for Non-Techies appeared first on DATAVERSITY. Moreover, complex usability helped in developing a network of certified (aka expensive and lucrative) consultancy workforce. IT has recently experienced […].

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Dataconomy

JUNE 1, 2023

Microsoft has made good on its promise to deliver a simplified and more efficient Microsoft Fabric price model for its end-to-end platform designed for analytics and data workloads. Microsoft’s unified pricing model for the Fabric suite marks a significant advancement in the analytics and data market.

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Power BI Data Lakes Azure Data Silos 194

Data Science Dojo

SEPTEMBER 11, 2024

Microsoft Fabric aims to reduce unnecessary data replication, centralize storage, and create a unified environment with its unique data fabric method. Microsoft Fabric is a cutting-edge analytics platform that helps data experts and companies work together on data projects. What is Microsoft Fabric?

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Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

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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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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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Dataconomy

MARCH 4, 2025

Data mining refers to the systematic process of analyzing large datasets to uncover hidden patterns and relationships that inform and address business challenges. It’s an integral part of data analytics and plays a crucial role in data science. Each stage is crucial for deriving meaningful insights from data.

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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. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cloud Data Analytics Analytics 58

Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data.

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SQL AWS Data Lakes AI 160

Dataversity

SEPTEMBER 5, 2024

… and your data warehouse / data lake / data lakehouse. A few months ago, I talked about how nearly all of our analytics architectures are stuck in the 1990s. Maybe an executive at your company read that article, and now you have a mandate to “modernize analytics.”

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Analytics Analytics Data Lakes Data Warehouse 52

Data Science Blog

JULY 20, 2024

Es bietet vollständige Automatisierung des BI-Stacks und unterstützt ein breites Spektrum an Data Warehouses, analytischen Datenbanken und Frontends. Automatisierung: Erstellt SQL-Code, DACPAC-Dateien, SSIS-Pakete, Data Factory-ARM-Vorlagen und XMLA-Dateien. Data Lakes: Unterstützt MS Azure Blob Storage.

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Azure SQL Power BI Data Lakes 130

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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Data Lakes Data Modeling Data Models Data Warehouse 52

Dataversity

MAY 28, 2024

Most enterprises today store and process vast amounts of data from various sources within a centralized repository known as a data warehouse or data lake, where they can analyze it with advanced analytics tools to generate critical business insights.

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Analytics Analytics Data Warehouse Data Lakes 52

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Data Lakes Data Governance Data Warehouse Business Intelligence 52

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. March 30, 2021.

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phData

NOVEMBER 8, 2024

The most used open table formats currently are Apache Iceberg, Delta Lake, and Apache Hudi. These systems are built on open standards and offer immense analytical and transactional processing flexibility. Adopting an Open Table Format architecture is becoming indispensable for modern data systems. Why are They Essential?

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Data Lakes Data Warehouse Database Azure 52

phData

APRIL 4, 2023

Fivetran today announced support for Amazon Simple Storage Service (Amazon S3) with Apache Iceberg data lake format. Amazon S3 is an object storage service from Amazon Web Services (AWS) that offers industry-leading scalability, data availability, security, and performance.

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