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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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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Analytics Vidhya

JANUARY 7, 2022

By their definition, the types of data it stores and how it can be accessible to users differ. This article will discuss some of the features and applications of data warehouses, data marts, and data […]. The post Data Warehouses, Data Marts and Data Lakes appeared first on Analytics Vidhya.

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insideBIGDATA

JULY 4, 2023

In this article, Ashutosh Kumar discusses the emergence of modern data solutions that have led to the development of ELT and ETL with unique features and advantages. ELT is more popular due to its ability to handle large and unstructured datasets like in data lakes.

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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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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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KDnuggets

JANUARY 16, 2023

In this article, we will discuss the benefits of using SQL with a data lake and how it can help organizations unlock the full potential of their data.

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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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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 167

KDnuggets

JANUARY 16, 2020

Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility.

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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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Data Lakes Data Warehouse Database Data Science 98

Dataconomy

FEBRUARY 21, 2020

High quality, reliable data forms the backbone for all successful data endeavors, from reporting and analytics to machine learning. Delta Lake is an open-source storage layer that solves many concerns around data. The post How to make data lakes reliable appeared first on Dataconomy.

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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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Dataversity

MARCH 26, 2024

Writing data to an AWS data lake and retrieving it to populate an AWS RDS MS SQL database involves several AWS services and a sequence of steps for data transfer and transformation. This process leverages AWS S3 for the data lake storage, AWS Glue for ETL operations, and AWS Lambda for orchestration.

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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. Data Type and Processing.

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Data Lakes Data Warehouse ETL Data Scientist 140

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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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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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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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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Data Lakes Data Warehouse Business Intelligence Business Intelligence 91

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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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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Smart Data Collective

SEPTEMBER 23, 2020

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. Both data warehouses and data lakes are used when storing big data.

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Data Lakes Data Warehouse Big Data Big Data 105

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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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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Dataconomy

JULY 23, 2018

Since data has been called the “oil” of the new economy, it’s easy to assume that more is better. You can never have too much oil, so the same goes for data too, right? Hence there has been a lot of hype about data lakes over the past few years.

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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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ODSC - Open Data Science

SEPTEMBER 29, 2023

Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

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databricks

JANUARY 26, 2023

We thank Vishnu Vettrivel, Founder, and Alex Thomas, Principal Data Scientist, for their contributions. This is a collaborative post from Databricks and wisecube.ai.

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Data Lakes Data Scientist 276

Analytics Vidhya

DECEMBER 1, 2021

Image Source: GitHub Table of Contents What is Data Engineering? Components of Data Engineering Object Storage Object Storage MinIO Install Object Storage MinIO Data Lake with Buckets Demo Data Lake Management Conclusion References What is Data Engineering?

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Analytics Vidhya

JULY 29, 2022

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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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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Tableau

JULY 28, 2021

Our technology partner Dremio offers a next-generation data lake engine to securely query a customer’s cloud data lake storage directly. An increasing number of customers have adopted data lakes as the foundation of their data platform. Get started using the native Dremio connector today.

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Dataversity

OCTOBER 14, 2022

The data being talked about is useful for businesses to draw insights, formulate strategies, and understand trends and customer behavior, among others. […]. The post Maximize the ROI of Your Enterprise Data Lake appeared first on DATAVERSITY.

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Smart Data Collective

APRIL 24, 2020

Perhaps one of the biggest perks is scalability, which simply means that with good data lake ingestion a small business can begin to handle bigger data numbers. The reality is businesses that are collecting data will likely be doing so on several levels. Proper Scalability. Uses Powerful Algorithms.

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Data Lakes Algorithm Deep Learning Deep Learning 98

databricks

JUNE 6, 2023

Apache Parquet is one of the most popular open source file formats in the big data world today. Being column-oriented, Apache Parquet allows.

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Data Lakes Big Data Big Data Data Engineering 187

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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