Adrian Bridgwater for Forbes

MARCH 27, 2023

The data lakehouse is a hybrid term used to denote some of the structures we would find in a more ordered data warehouse with the expansiveness and lower cost functionality of the data lake. But, finding our way around the data lakehouse, even with its defined edges and channels can still be tough.

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Data Lakes Data Warehouse Big Data Big Data 255

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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Data Lakes Azure Analytics Analytics 336

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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Data Lakes Data Warehouse Big Data Big Data 131

Adrian Bridgwater for Forbes

FEBRUARY 16, 2023

Part of the universe of virtual data topologies, a data lakehouse combines the expansive and unstructured raw data reserves we find in the data lake (that place we use to ‘pour’ data into, often before we know what to do with it)… and the more structured and ordered world of the data warehouse.

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Data Lakes Data Warehouse Big Data Big Data 233

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. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

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Data Lakes Data Warehouse Database Big Data 98

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.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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Data Engineering Data Engineer Data Engineering Data Engineering 195

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 116

Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

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Data Lakes Business Intelligence Business Intelligence Analytics 315

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Flipboard

APRIL 17, 2023

Enterprises often rely on data warehouses and data lakes to handle big data for various purposes, from business intelligence to data science. A new approach, called a data lakehouse, aims to …

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Data Lakes Data Warehouse Big Data Big Data 123

Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The term and its underlying technology have been thriving more than ever.

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Data Lakes Data Warehouse Data Quality Data Governance 59

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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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Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

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Data Warehouse Data Lakes Database Big Data 112

Tableau

JUNE 8, 2021

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

Tableau 102

Tableau Data Lakes Data Warehouse SQL 102

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. Implementing data security measures Data security is a critical aspect of data engineering.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

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Power BI Data Lakes Azure Data Silos 194

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. The destination is decided by the use case of the data pipeline.

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Data Pipeline Data Warehouse ETL Exploratory Data Analysis 145

Women in Big Data

OCTOBER 9, 2024

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

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 […].

Data Lakes 59

Data Lakes Data Warehouse Big Data Big Data 59

Tableau

MARCH 30, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

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Azure Tableau Data Lakes SQL 102

Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Big Data Architect.

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SQL AWS Data Lakes AI 156

phData

NOVEMBER 8, 2024

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature.

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Data Lakes Data Warehouse Database Azure 52

ODSC - Open Data Science

JUNE 7, 2023

Data has to be stored somewhere. Data warehouses are repositories for your cleaned, processed data, but what about all that unstructured data your organization is starting to notice? What is a data lake? This can be structured, semi-structured, and even unstructured data. Where does it go?

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Those are the big data science announcements of the week. Azure Synapse.

Data Science 106

Data Science Azure SQL Machine Learning 106

IBM Journey to AI blog

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. How does an open data lakehouse architecture support AI? All of this supports the use of AI.

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Data Lakes Data Warehouse AI AI 95

Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data.

Data Analysis 145

Data Analysis Data Analysis Analytics Analytics 145

Pickl AI

SEPTEMBER 18, 2024

Summary: Netflix’s sophisticated Big Data infrastructure powers its content recommendation engine, personalization, and data-driven decision-making. As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions.

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

ODSC - Open Data Science

MAY 7, 2024

In this episode, James Serra, author of “Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh” joins us to discuss his book and dive into the current state and possible future of data architectures.

Data Warehouse 52

Data Warehouse Data Lakes Data Science Big Data 52

Tableau

JUNE 8, 2021

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

Tableau 52

Tableau Data Lakes Data Warehouse SQL 52

Dataconomy

SEPTEMBER 4, 2023

Big data analytics: Big data analytics is designed to handle massive volumes of data from various sources, including structured and unstructured data. Big data analytics is essential for organizations dealing with large-scale data, such as social media platforms, e-commerce giants, and scientific research.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This is also true that decentralized data management is not new.

Data Lakes 75

Data Lakes Hadoop Data Silos Data Warehouse 75

Tableau

MARCH 29, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

Azure 52

Azure Tableau Data Lakes SQL 52

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

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ETL Data Warehouse Data Quality Data Lakes 52

IBM Journey to AI blog

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Data Warehouse 58

Data Warehouse Data Engineering Data Engineering Data Engineering 58