Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction We are all pretty much familiar with the common modern cloud data warehouse model, which essentially provides a platform comprising a data lake (based on a cloud storage account such as Azure Data Lake Storage Gen2) AND a data warehouse compute engine […].

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Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources.

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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

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.

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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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insideBIGDATA

APRIL 22, 2024

In this contributed article, Sida Shen, product marketing manager, CelerData, discusses how data lakehouse architectures promise the combined strengths of data lakes and data warehouses, but one question arises: why do we still find the need to transfer data from these lakehouses to proprietary data warehouses?

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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

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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Adrian Bridgwater for Forbes

MARCH 27, 2023

The data lakehouse is a hybrid term used to denote some of the structures we would find in a more ordered data warehouse with the expansiveness and lower cost functionality of the data lake. But, finding our way around the data lakehouse, even with its defined edges and channels can still be tough.

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Dataconomy

NOVEMBER 1, 2017

Anderson, Talend Regional Manager, Customer Success Architect & Kent Graziano, Snowflake Senior Technical Evangelist So you want to build a Data Lake? Perhaps you think a Data Lake will eliminate the need for a Data Warehouse and all your business users will merely. Ok, sure let’s talk about that.

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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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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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Adrian Bridgwater for Forbes

FEBRUARY 16, 2023

Part of the universe of virtual data topologies, a data lakehouse combines the expansive and unstructured raw data reserves we find in the data lake (that place we use to ‘pour’ data into, often before we know what to do with it)… and the more structured and ordered world of the data warehouse.

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The Data Administration Newsletter

SEPTEMBER 14, 2021

Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, “a data lake is a storage repository that holds an enormous amount of raw or refined data in native format until it is accessed.” That makes sense. I think the […].

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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

FEBRUARY 7, 2023

Schon damals in Ansätzen, aber spätestens heute gilt es zu recht als Best Practise, die Datenanbindung an ein Data Warehouse zu machen und in diesem die Daten für die Reports aufzubereiten. Ein Data Warehouse ist eine oder eine Menge von Datenbanken. Was gerade zum Trend wird, ist der Aufbau eines Data Lakehouses.

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Analytics Vidhya

OCTOBER 10, 2022

Introduction In the modern data world, Lakehouse has become one of the most discussed topics for building a data platform. Enterprises have slowly started adopting Lakehouses for their data ecosystems as they offer cost efficiencies of data lakes and the performance of warehouses. […].

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Dataversity

SEPTEMBER 20, 2024

However, the sheer volume, variety, and velocity of data can overwhelm traditional data management solutions. Enter the data lake – a centralized repository designed to store all types of data, whether structured, semi-structured, or unstructured.

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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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Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It is often used as a foundation for enterprise data lakes.

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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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Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

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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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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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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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Hacker News

MARCH 28, 2024

A unified SQL query interface and portable runtime to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake. spiceai/spiceai

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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

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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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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Flipboard

APRIL 17, 2023

Enterprises often rely on data warehouses and data lakes to handle big data for various purposes, from business intelligence to data science. A new approach, called a data lakehouse, aims to … But these architectures have limitations and tradeoffs that make them less than ideal for modern teams.

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Dataversity

JANUARY 25, 2023

The emergence of advanced data storage technologies, such as cloud computing, data hubs, and data lakes, makes us question the role of traditional data warehouses in modern data architecture. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant?

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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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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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Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

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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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The Data Administration Newsletter

JANUARY 3, 2023

For a while now, vendors have been advocating that people put their data in a data lake when they put their data in the cloud. The Data Lake The idea is that you put your data into a data lake. Then, at a later point in time, the end user analyst can come along and […].

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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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