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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ODSC - Open Data Science

AUGUST 15, 2023

Recently we’ve seen lots of posts about a variety of different file formats for data lakes. There’s Delta Lake, Hudi, Iceberg, and QBeast, to name a few. It can be tough to keep track of all these data lake formats — let alone figure out why (or if!) And I’m curious to see if you’ll agree.

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Data Lakes ETL Data Science Algorithm 98

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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Analytics Vidhya

OCTOBER 4, 2022

This article was published as a part of the Data Science Blogathon. Introduction Today, Data Lake is most commonly used to describe an ecosystem of IT tools and processes (infrastructure as a service, software as a service, etc.) that work together to make processing and storing large volumes of data easy.

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Analytics Vidhya

AUGUST 10, 2022

Introduction You can access your Azure Data Lake Storage Gen1 directly with the RapidMiner Studio. This is the feature offered by the Azure Data Lake Storage connector. The post Connecting and Reading Data From Azure Data Lake appeared first on Analytics Vidhya.

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Data Lakes Azure Data Science Analytics 124

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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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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Analytics Vidhya

OCTOBER 28, 2022

Data collection is critical for businesses to make informed decisions, understand customers’ […]. The post Data Lake or Data Warehouse- Which is Better? We can use it to represent facts, figures, and other information that we can use to make decisions. appeared first on Analytics Vidhya.

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Data Lakes Data Warehouse Data Science Analytics 117

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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Data Lakes Data Warehouse Data Governance Data Quality 98

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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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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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 Lakes Azure Data Science Analytics 111

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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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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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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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 Lakes Azure Data Science Big Data 87

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 Lakes Data Science Big Data Big Data 90

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 Lakes Azure Big Data Analytics Big Data Analytics 96

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

IBM Journey to AI blog

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

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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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Data Lakes Data Warehouse Analytics Analytics 83

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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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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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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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of 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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Data Lakes Data Warehouse Analytics Analytics 115

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 Lakes AWS Data Science Analytics 103

Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

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Data Lakes Data Warehouse Hadoop Data Scientist 59

Dataversity

JUNE 18, 2021

In my recent blog series, I delved into one of 2021’s hottest data topics – data democratization – exploring how it can fit into a business’ overarching data strategy along with some practical advice on how to implement […]. The post Could the Data Mesh Solve Your Data Lake Scaling Issues?

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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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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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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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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 96

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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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

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

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Dataversity

AUGUST 19, 2022

The data we produce and manage is growing in scale and demands careful consideration of the proper data framework for the job. There’s no one-size-fits-all data architecture, and […]. The post Data Lakes Are Dead: Evolving Your Company’s Data Architecture appeared first on DATAVERSITY.

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Data Lakes Data Governance Data Quality 52