AWS Big Data

OCTOBER 30, 2024

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. To start the job, choose Run. format(dbname)).config("spark.sql.catalog.glue_catalog.catalog-impl",

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Data Lake Data Processing Optimization Machine Learning 101

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. However, it also offers additional optimizations that you can use to further improve this performance and achieve even faster query response times from your data warehouse.

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David Menninger's Analyst Perspectives

JANUARY 22, 2021

Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data.

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Data Lake IT Data Warehouse Data Governance 269

Analytics Vidhya

MARCH 12, 2025

In this article, we will explore the evolution of Iceberg, its key features like ACID transactions, partition evolution, and time travel, and how it integrates with modern data lakes. Well also dive into […] The post How to Use Apache Iceberg Tables? appeared first on Analytics Vidhya.

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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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CIO Business Intelligence

DECEMBER 20, 2024

United claims to be among the earliest users of the Amazon SageMaker ML platform, and it has leveraged its own United Data Hub and AWS Bedrock-based Mars ML platform to create this first batch of production gen AI LLMs. People hear the specifics, and they understand it and their blood pressure goes down.

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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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AWS Big Data

NOVEMBER 22, 2024

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. Using Athena and the dbt adapter, you can transform raw data in Amazon S3 into well-structured tables suitable for analytics.

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Data Lake Data Warehouse Cost-Benefit Data Transformation 84

KDnuggets

FEBRUARY 5, 2024

How and why the data lake architecture often fails to meet its promises. And how better governance helps mitigate such challenges.

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Data Lake IT 135

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. Both are seeing strong growth.

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Data Lake Machine Learning Data Warehouse Modeling 361

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 341

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O'Reilly on Data

OCTOBER 19, 2021

Why: Data Makes It Different. In contrast, a defining feature of ML-powered applications is that they are directly exposed to a large amount of messy, real-world data which is too complex to be understood and modeled by hand. However, the concept is quite abstract. Can’t we just fold it into existing DevOps best practices?

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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. They are the same.

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Data Lake Metadata Snapshot Recreation/Entertainment 116

David Menninger's Analyst Perspectives

JANUARY 15, 2021

Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data.

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IT Data Architecture Big Data Data Processing 306

DataKitchen

DECEMBER 9, 2024

We will cover four parts: establishing the infrastructure, getting the data, iterating and automating, and using small, empowered teams. They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. It is necessary to have more than a data lake and a database.

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Data Quality Data Lake Testing Statistics 161

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

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.

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Data Lake Data Warehouse Recreation/Entertainment Data-driven 102

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

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Data Lake Data Warehouse Visualization Snapshot 122

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 user can query data from any of the cloud stores.

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Data Lake Analytics Cost-Benefit Management 112

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.

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Data Lake Metadata Statistics Optimization 125

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.

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Data Lake Testing Big Data Management 129

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.

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Data Lake Data Warehouse Data Governance Publishing 109

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.

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Data Lake Publishing Metadata Data-driven 122

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.

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Data Lake Statistics Broadcasting Optimization 105

AWS Big Data

JUNE 10, 2024

A modern data strategy redefines and enables sharing data across the enterprise and allows for both reading and writing of a singular instance of the data using an open table format. Why Cloudinary chose Apache Iceberg Apache Iceberg is a high-performance table format for huge analytic workloads.

Data Lake 122

Data Lake Metadata Snapshot Analytics 122

David Menninger's Analyst Perspectives

SEPTEMBER 22, 2022

But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time. Many organizations can’t take full advantage of their data lakes because they don’t know what data actually exists.

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Data Lake Business Intelligence Analytics IT 278

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.

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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. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

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Data Lake Marketing Data Processing Management 112

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. Eventually, transactional data lakes emerged to add transactional consistency and performance of a data warehouse to the data lake.

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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. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

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Data Lake Data Warehouse Data-driven Optimization 82

AWS Big Data

SEPTEMBER 26, 2024

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging. Let’s walk through the architecture chronologically for a closer look at each step.

Data Lake 101

Data Lake Cost-Benefit Unstructured Data Modeling 101

AWS Big Data

APRIL 3, 2024

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. This post is co-written with Andries Engelbrecht and Scott Teal from Snowflake.

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Data Lake Snapshot Metadata Data Architecture 106

CIO Business Intelligence

AUGUST 6, 2024

La firma de consultoría también deberá crear un data lake que permita almacenar y compartir fácilmente los datos de todo el ecosistema deportivo español, para lograr sinergias en torno a los distintos proyectos que se realicen.

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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.

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AWS Big Data

OCTOBER 29, 2024

With over 10 PB of data across 1,500 data assets, 1,000 data use cases, and more than 9000 users, the BMW CDH has become a resounding success since BMW decided to build it in a strategic collaboration with Amazon Web Services (AWS) in 2020. This led to inefficiencies in data governance and access control.

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Data Lake Sales Metadata Machine Learning 89