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.

Data Lake 289

Data Lake Data Warehouse Management Analytics 289

AWS Big Data

NOVEMBER 8, 2024

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. Customers use data lake tables to achieve cost effective storage and interoperability with other tools.

Data Lake 97

Data Lake Data Warehouse Optimization Testing 97

David Menninger's Analyst Perspectives

OCTOBER 26, 2021

Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. The platform supports streaming data, SQL queries, graph processing and machine learning.

Big Data 327

Big Data Data Processing Machine Learning Modeling 327

AWS Big Data

NOVEMBER 22, 2024

At AWS, we are committed to empowering organizations with tools that streamline data analytics and transformation processes. This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience.

Data Lake 84

Data Lake Data Warehouse Cost-Benefit Data Transformation 84

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.

Data Lake 336

Data Lake Analytics Data Warehouse IT 336

AWS Big Data

DECEMBER 4, 2024

This week on the keynote stages at AWS re:Invent 2024, you heard from Matt Garman, CEO, AWS, and Swami Sivasubramanian, VP of AI and Data, AWS, speak about the next generation of Amazon SageMaker , the center for all of your data, analytics, and AI. The relationship between analytics and AI is rapidly evolving.

Data Analytics 86

Data Analytics Analytics Data Lake Data Quality 86

AWS Big Data

MARCH 13, 2025

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. It enables teams to securely find, prepare, and collaborate on data assets and build analytics and AI applications through a single experience, accelerating the path from data to value.

Analytics 92

Analytics Data Lake Data Warehouse Data-driven 92

AWS Big Data

MARCH 18, 2024

Many organizations operate data lakes spanning multiple cloud data stores. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics processes. This serves as the S3 data lake data for this post.

Data Lake 112

Data Lake Analytics Cost-Benefit Management 112

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

Visualization 116

Visualization Data Lake Testing Data Governance 116

AWS Big Data

OCTOBER 30, 2024

With this integration, you can now seamlessly query your governed data lake assets in Amazon DataZone using popular business intelligence (BI) and analytics tools, including partner solutions like Tableau. Choose Connect with JDBC. In the JDBC parameters dialog box, select Using IDC auth and copy the JDBC URL.

Analytics 104

Analytics Visualization Data Governance Data-driven 104

AWS Big Data

JUNE 10, 2024

In this blog post, we dive into different data aspects and how Cloudinary breaks the two concerns of vendor locking and cost efficient data analytics by using Apache Iceberg, Amazon Simple Storage Service (Amazon S3 ), Amazon Athena , Amazon EMR , and AWS Glue.

Data Lake 122

Data Lake Metadata Snapshot Analytics 122

AWS Big Data

JANUARY 6, 2025

Google Analytics 4 (GA4) provides valuable insights into user behavior across websites and apps. But what if you need to combine GA4 data with other sources or perform deeper analysis? It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Analytics 94

Analytics Data Warehouse Big Data Metrics 94

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.

Data Lake 315

Data Lake Business Intelligence Enterprise Analytics 315

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.

Data Lake 116

Data Lake Cost-Benefit Data Warehouse Big Data 116

AWS Big Data

OCTOBER 3, 2023

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 116

Data Lake Metadata Snapshot Recreation/Entertainment 116

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 125

Data Lake Metadata Statistics Optimization 125

AWS Big Data

NOVEMBER 26, 2024

Initially, data warehouses were the go-to solution for structured data and analytical workloads but were limited by proprietary storage formats and their inability to handle unstructured data. In practice, OTFs are used in a broad range of analytical workloads, from business intelligence to machine learning.

Metadata 95

Metadata Data Lake Snapshot Data Warehouse 95

David Menninger's Analyst Perspectives

MAY 13, 2019

Organizations now must store, process and use data of significantly greater volume and variety than in the past.

Business Analytics 180

Business Analytics Big Data Analytics Enterprise 180

AWS Big Data

AUGUST 15, 2024

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.

Data Lake 109

Data Lake Data Warehouse Data Governance Publishing 109

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 129

Data Lake Testing Big Data Management 129

AWS Big Data

OCTOBER 10, 2024

Amazon Redshift has established itself as a highly scalable, fully managed cloud data warehouse trusted by tens of thousands of customers for its superior price-performance and advanced data analytics capabilities. This allows you to maintain a comprehensive view of your data while optimizing for cost-efficiency.

Data Lake 102

Data Lake Data Warehouse Recreation/Entertainment Data-driven 102

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. However, efficiently managing and synchronizing data within these lakes presents a significant challenge.

Data Lake 112

Data Lake Marketing Data Processing Management 112

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.

Data Lake 116

Data Lake Sales Data Warehouse Snapshot 116

AWS Big Data

SEPTEMBER 10, 2024

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

Data Lake 107

Data Lake Metadata Management Software 107

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 128

Data Lake Data Processing Metadata Snapshot 128

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. This allowed customers to scale read analytics workloads and offered isolation to help maintain SLAs for business-critical applications.

Data Lake 82

Data Lake Data Warehouse Data-driven Optimization 82

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 98

Data Integration Data Lake Statistics Data-driven 98

AWS Big Data

AUGUST 31, 2023

Tens of thousands of customers today use Amazon Redshift to analyze exabytes of data and run analytical queries, making it the most widely used cloud data warehouse. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 108

Data Lake Data Warehouse Metadata Data Architecture 108

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 105

Data Lake Statistics Broadcasting Optimization 105

AWS Big Data

APRIL 8, 2025

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. About the Authors Sotaro Hikita is an Analytics Solutions Architect. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Snapshot 117

Snapshot Management Metadata Big Data 117

AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

Data Lake 106

Data Lake Snapshot Metadata Data Architecture 106

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

Data Lake 94

Data Lake Metrics Testing Cost-Benefit 94

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 122

Data Lake Publishing Metadata Data-driven 122

AWS Big Data

DECEMBER 20, 2024

The DataFrame code generation now extends beyond AWS Glue DynamicFrame to support a broader range of data processing scenarios. He is devoted to designing and building end-to-end solutions to address customers data analytic and processing needs with cloud-based, data-intensive technologies.

Data Integration 94

Data Integration Visualization Data Processing Data Lake 94

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. Enhance agility by localizing changes within business domains and clear data contracts. Eliminate centralized bottlenecks and complex data pipelines.

IoT 101

IoT Machine Learning Metadata Data-driven 101