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 291

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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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

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

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 Warehouse Data Lakes Analytics Analytics 289

Dataconomy

FEBRUARY 21, 2020

Data professionals across industries recognize they must effectively harness data for their businesses to innovate and gain competitive advantage. High quality, reliable data forms the backbone for all successful data endeavors, from reporting and analytics to machine learning.

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Data Lakes Machine Learning Machine Learning Analytics 225

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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Analytics Vidhya

DECEMBER 1, 2021

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? The post How to Implement Data Engineering in Practice? appeared first on Analytics Vidhya.

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insideBIGDATA

AUGUST 28, 2024

Dremio, the unified lakehouse platform for self-service analytics and AI, announced a breakthrough in data lake analytics performance capabilities, extending its leadership in self-optimizing, autonomous Iceberg data management.

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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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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? Selecting one among […].

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Data Lakes Hadoop Data Science Analytics 350

Hacker News

APRIL 30, 2024

Today Crunchy Data announces a new analytics engine to read cloud object storage files like CSV, JSON, and Parquet with Postgres.

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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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Data Lakes Data Science Analytics Analytics 358

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 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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ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Flipboard

NOVEMBER 22, 2024

It enables different business units within an organization to create, share, and govern their own data assets, promoting self-service analytics and reducing the time required to convert data experiments into production-ready applications. We discuss this in more detail later in this post.

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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. Data Analytics Simplified. Proper Scalability.

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Dataconomy

APRIL 13, 2021

Data professionals have long debated the merits of the data lake versus the data warehouse. But this debate has become increasingly intense in recent times with the prevalence of data and analytics workloads in the cloud, the growing frustration with the brittleness of Hadoop, and hype around a new architectural.

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Smart Data Collective

APRIL 2, 2019

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

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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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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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KDnuggets

JANUARY 18, 2023

7 Best Platforms to Practice SQL • Explainable AI: 10 Python Libraries for Demystifying Your Model's Decisions • ChatGPT: Everything You Need to Know • Data Lakes and SQL: A Match Made in Data Heaven • Google Data Analytics Certification Review for 2023

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insideBIGDATA

SEPTEMBER 7, 2023

Starburst, the data lake analytics platform, today extended their support for the most widely used multi-purpose, high-level programming language, Python with PyStarburst, as well as announced a new integration with the open source Python library, Ibis, built in collaboration with composable data systems builder and Ibis maintainer, Voltron Data. (..)

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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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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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Data Science Blog

MAY 20, 2024

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. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL.

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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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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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Tableau

JULY 28, 2021

Our mission at Tableau is to help customers see and understand their data. To accomplish this, customers need to be able to access whatever data is important to their analytic needs, wherever it lives. An increasing number of customers have adopted data lakes as the foundation of their data platform.

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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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Dataconomy

NOVEMBER 24, 2019

An aspiration to create a data-driven future has resulted in massive data lakes, where even the most experienced data scientists can drown in. Today, it’s all about what you do with that data that determines your success. Without data, you simply can’t. And IBM has the recipe for this.

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Precisely

JANUARY 9, 2025

Data marts soon evolved as a core part of a DW architecture to eliminate this noise. Data marts involved the creation of built-for-purpose analytic repositories meant to directly support more specific business users and reporting needs (e.g., financial reporting, customer analytics, supply chain management). A data lake!

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Dataconomy

SEPTEMBER 23, 2024

In today’s digital era, data is the key that allows companies to unlock better decision-making, understand customer behavior and optimize campaigns. However, simply acquiring all available data and storing it in data lakes does not guarantee success.

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Dataconomy

DECEMBER 24, 2021

For decades, managing data essentially meant collecting, storing, and occasionally accessing it. That has all changed in recent years, as businesses look for the critical information that can be pulled from the massive amounts of data being generated, accessed, and stored in myriad locations, from corporate data centers to the cloud.

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