Analytics Vidhya

MAY 30, 2022

Azure Data Lake Storage is capable of storing large quantities of structured, semi-structured, and unstructured data in […]. The post Introduction to Azure Data Lake Storage Gen2 appeared first on Analytics Vidhya. Introduction ADLS Gen2 The ADLS Gen2 service is built upon Azure Storage as its foundation.

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Data Lake Unstructured Data Data Science Publishing 344

Analytics Vidhya

DECEMBER 20, 2022

Before seeing the practical implementation of the use case, let’s briefly introduce Azure Data Lake Storage Gen2 and the Paramiko module. Introduction to Azure Data Lake Storage Gen2 Azure Data Lake Storage Gen2 is a data storage solution specially designed for big data […].

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Data Lake Big Data Data Science Publishing 266

Analytics Vidhya

AUGUST 31, 2022

This article was published as a part of the Data Science Blogathon. Introduction A data lake is a central data repository that allows us to store all of our structured and unstructured data on a large scale. The post A Detailed Introduction on Data Lakes and Delta Lakes appeared first on Analytics Vidhya.

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Data Lake Unstructured Data Big Data Dashboards 269

David Menninger's Analyst Perspectives

MAY 7, 2020

In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends. He explores the relationship between data warehouses and data lakes and share some of Ventana Research’s findings on the subject.

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Data Lake Data Warehouse Risk Marketing 287

Analytics Vidhya

FEBRUARY 2, 2023

Now, businesses are looking for different types of data storage to store and manage their data effectively. Organizations can collect millions of data, but if they’re lacking in storing that data, those efforts […] The post A Comprehensive Guide to Data Lake vs. Data Warehouse appeared first on Analytics Vidhya.

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Data Lake Data Warehouse Management Analytics 272

Analytics Vidhya

OCTOBER 21, 2020

Overview Understand the meaning of data lake and data warehouse We will see what are the key differences between Data Warehouse and Data Lake. The post What are the differences between Data Lake and Data Warehouse? appeared first on Analytics Vidhya.

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Analytics Vidhya

APRIL 25, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Data Lake architecture for different use cases – Elegant. The post A Guide to Build your Data Lake in AWS appeared first on Analytics Vidhya.

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Data Lake Data Science Publishing Analytics 291

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 Lake Unstructured Data Management Analytics 178

AWS Big Data

OCTOBER 30, 2024

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. Delete the bucket.

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Data Lake Data Processing Optimization Machine Learning 95

AWS Big Data

NOVEMBER 8, 2024

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. Customers use data lake tables to achieve cost effective storage and interoperability with other tools.

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Data Lake Data Warehouse Optimization Testing 90

CIO Business Intelligence

OCTOBER 24, 2024

En este sentido, Telefónica Tech, en colaboración con Xylem e Ídrica, está desarrollando la infraestructura tecnológica para la creación del data lake que permitirá al Principado de Asturias optimizar la gestión, el análisis avanzado y la visualización de sus recursos hídricos, así como aplicar algoritmia para poder prevenir diferentes escenarios.

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Data Lake Data Architecture Management 110

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

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Data Lake Statistics Broadcasting Optimization 98

AWS Big Data

OCTOBER 3, 2023

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. They are the same.

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Data Lake Metadata Snapshot Recreation/Entertainment 110

AWS Big Data

MARCH 18, 2024

Many organizations operate data lakes spanning multiple cloud data stores. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics processes. Upload the data file to the S3 bucket created by the CloudFormation stack.

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Data Lake Analytics Cost-Benefit Management 105

AWS Big Data

SEPTEMBER 10, 2024

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

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Data Lake Metadata Management Software 102

AWS Big Data

SEPTEMBER 26, 2024

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging. About the Authors Dave Horne is a Sr.

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Data Lake Cost-Benefit Unstructured Data Modeling 92

AWS Big Data

AUGUST 15, 2024

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.

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Data Lake Data Warehouse Data Governance Publishing 102

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. Data Type and Processing.

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Data Lake Data Warehouse Unstructured Data Structured Data 140

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

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Data Lake Marketing Management Data Processing 107

KDnuggets

OCTOBER 30, 2023

A comparative overview of data warehouses, data lakes, and data marts to help you make informed decisions on data storage solutions for your data architecture.

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Data Lake Data Warehouse Data Architecture 131

AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

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Data Lake Snapshot Metadata Data Architecture 100

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

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Data Lake Data Warehouse Visualization Snapshot 115

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

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Data Lake Metrics Testing Cost-Benefit 88

KDnuggets

FEBRUARY 5, 2024

How and why the data lake architecture often fails to meet its promises. And how better governance helps mitigate such challenges.

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Data Lake IT 113

CIO Business Intelligence

AUGUST 6, 2024

La firma de consultoría también deberá crear un data lake que permita almacenar y compartir fácilmente los datos de todo el ecosistema deportivo español, para lograr sinergias en torno a los distintos proyectos que se realicen.

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Data Lake Software Digital Transformation Strategy 110

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

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Data Lake Metadata Publishing Data-driven 116

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 Lake Cost-Benefit Data Warehouse Big Data 106

ScienceSoft

JULY 8, 2024

We look at different approaches to data lake design and implementation and contemplate if there exists a preferred technology among the available stack.

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Data Lake Technology 52

TDAN

JUNE 5, 2024

In the ever-evolving landscape of data management, two key concepts have emerged as essential components for organizations seeking to harness the power of their data: data marts and data lakes. Understanding the distinctions […]

Data Lake 52

Data Lake Management Data Architecture Big Data 52

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

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Data Lake Testing Big Data Management 126