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 271

Analytics Vidhya

DECEMBER 20, 2022

This article was published as a part of the Data Science Blogathon. Before seeing the practical implementation of the use case, let’s briefly introduce Azure Data Lake Storage Gen2 and the Paramiko module. The post An Overview of Using Azure Data Lake Storage Gen2 appeared first on Analytics Vidhya.

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Data Lake Big Data Data Science Publishing 271

Analytics Vidhya

DECEMBER 1, 2021

This article was published as a part of the Data Science Blogathon. 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

This article was published as a part of the Data Science Blogathon. The post How a Delta Lake is Process with Azure Synapse Analytics appeared first on Analytics Vidhya.

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Data Lake Data Warehouse Analytics Data Science 398

Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. 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. Selecting one among […].

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Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction In the modern data world, Lakehouse has become one of the most discussed topics for building a data platform.

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Data Lake Data Science Publishing Enterprise 358

O'Reilly on Data

FEBRUARY 19, 2021

The Right Solution for Your Data: Cloud Data Lakes and Data Lakehouses. Data lakes have experienced a fairly robust resurgence over the last few years, specifically cloud data lakes. A Wave of Cloud-Native, Distributed Data Frameworks.

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Data Lake Machine Learning Data Warehouse Modeling 362

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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CIO Business Intelligence

DECEMBER 6, 2024

It combines SQL analytics, data processing, AI development, data streaming, business intelligence, and search analytics. Another offering that AWS announced to support the integration is the SageMaker Data Lakehouse , aimed at helping enterprises unify data across Amazon S3 data lakes and Amazon Redshift data warehouses.

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Data Analytics Data Lake Analytics Data Warehouse 122

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Data Lake Sales Data Warehouse Snapshot 116

AWS Big Data

JUNE 10, 2024

Various data pipelines process these logs, storing petabytes (PBs) of data per month, which after processing data stored on Amazon S3, are then stored in Snowflake Data Cloud. Until recently, this data was mostly prepared by automated processes and aggregated into results tables, used by only a few internal teams.

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Data Lake Metadata Snapshot Analytics 121

Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Those are the big data science announcements of the week.

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Data Science Machine Learning Data Lake Visualization 106

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.

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Data Science 101

NOVEMBER 11, 2019

Welcome to the first beta edition of Cloud Data Science News. This will cover major announcements and news for doing data science in the cloud. Azure Synapse Analytics This is the future of data warehousing. Azure Synapse Analytics This is the future of data warehousing. Microsoft Azure.

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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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Data Science Machine Learning Analytics Data Lake 159

Sisense

DECEMBER 23, 2019

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. There just aren’t enough AI and data science practitioners to go around to tackle this lofty goal. Speaking of the demand, there’s another hurdle to AI success in the short-term.

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Data Lake Machine Learning Data Warehouse Digital Transformation 86

CIO Business Intelligence

MARCH 9, 2022

Despite the worldwide chaos, UAE national airline Etihad has managed to generate productivity gains and cost savings from insights using data science. Etihad began its data science journey with the Cloudera Data Platform and moved its data to the cloud to set up a data lake. Reem Alaya Lebhar.

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Data Science Data Lake Cost-Benefit Digital Transformation 98

AWS Big Data

DECEMBER 4, 2024

Amazon SageMaker Lakehouse , now generally available, unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. The tools to transform your business are here.

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Data Analytics Analytics Data Lake Data Quality 85

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

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Data-driven Data Governance Big Data Data Science 246

Data Science 101

DECEMBER 16, 2019

Even though Amazon is taking a break from announcements (probably focusing on Christmas shoppers), there are still some updates in the cloud data science world. If you would like to get the Cloud Data Science News as an email, you can sign up for the Cloud Data Science Newsletter. Here they are.

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Data Science Machine Learning Metadata Data Lake 81

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure?

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Machine Learning Data Science Data Lake Big Data 89

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

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Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

JUNE 20, 2023

It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. About the Authors Vivek Gautam is a Data Architect with specialization in data lakes at AWS Professional Services.

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Data Lake Data Science Recreation/Entertainment Data-driven 82

Corinium

APRIL 9, 2019

Even five years ago many companies were still asking the question, “What is Big Data?” We were consistently being told that data science would be the “ sexiest ” job of the century but finding a data scientist to implement a Big Data project was difficult to do.

Unstructured Data 150

Unstructured Data Data Lake Big Data Data Collection 150

O'Reilly on Data

OCTOBER 19, 2021

Similarly, it would be pointless to pretend that a data-intensive application resembles a run-off-the-mill microservice which can be built with the usual software toolchain consisting of, say, GitHub, Docker, and Kubernetes. Adapted from the book Effective Data Science Infrastructure. Data Science Layers.

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IT Testing Experimentation Software 364

David Menninger's Analyst Perspectives

OCTOBER 31, 2024

I previously wrote about the importance of open table formats to the evolution of data lakes into data lakehouses. The concept of the data lake was initially proposed as a single environment where data could be combined from multiple sources to be stored and processed to enable analysis by multiple users for multiple purposes.

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Data Lake Unstructured Data Data Warehouse Software 130

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

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Data Lake Testing Snapshot Big Data 80

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

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Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

AUGUST 3, 2023

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. For more information, see Changing the default settings for your data lake.

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Data Lake Visualization Dashboards Insurance 87

IBM Big Data Hub

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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Data Lake Metadata Cost-Benefit Data Warehouse 60

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

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Data Lake Data Warehouse Data Integration Management 59

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

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Data Architecture Management Consulting Internet of Things 122

CIO Business Intelligence

MAY 23, 2022

Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex. The reality is that the cloud is not a hammer that should be used to hit every AI nail. Potential headaches of DIY on-prem infrastructure.

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DataKitchen

AUGUST 9, 2021

Instead of having a giant, unwieldy data lake , the data mesh breaks up the data and workflow assets into controllable and composable domains with inherent interdependencies. Domains are built from raw data and/or the output of other domains. We call this collection of capabilities observable meta-orchestration.

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CIO Business Intelligence

NOVEMBER 25, 2022

As part of that transformation, Agusti has plans to integrate a data lake into the company’s data architecture and expects two AI proofs of concept (POCs) to be ready to move into production within the quarter. Today, we backflush our data lake through our data warehouse.

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Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

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