AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

Data Lake 127

Data Lake Snapshot Metadata Data Architecture 127

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.

Data Lake 137

Data Lake Data Warehouse Visualization Snapshot 137

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 122

Data Lake Data Warehouse Data Governance Publishing 122

AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

AWS Big Data

SEPTEMBER 4, 2024

Effective data analytics relies on seamlessly integrating data from disparate systems through identifying, gathering, cleansing, and combining relevant data into a unified format. This solution also allows you to update certain fields of the account object in the data lake and push it back to Salesforce.

Data Integration 109

Data Integration Data Lake Data-driven Cost-Benefit 109

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. 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 119

Data Lake Data Warehouse Metadata Data Architecture 119

AWS Big Data

MARCH 13, 2025

Unified access to your data is provided by Amazon SageMaker Lakehouse , a unified, open, and secure data lakehouse built on Apache Iceberg open standards. Now, theyre able to build and collaborate with their data and tools available in one experience, dramatically reducing time-to-value.

Analytics 93

Analytics Data Lake Data Warehouse Data-driven 93

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 111

Data Lake Metadata Management Software 111

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.

Data Lake 116

Data Lake Marketing Data Processing Management 116

AWS Big Data

DECEMBER 9, 2024

The importance of publishing only high-quality data cant be overstatedits the foundation for accurate analytics, reliable machine learning (ML) models, and sound decision-making. AWS Glue is a serverless data integration service that you can use to effectively monitor and manage data quality through AWS Glue Data Quality.

Data Quality 126

Data Quality Publishing Snapshot Data Lake 126

AWS Big Data

JUNE 10, 2024

Solving the small file problem and improving query performance In modern data architectures, stream processing engines such as Amazon EMR are often used to ingest continuous streams of data into data lakes using Apache Iceberg. Iceberg provides several maintenance operations to keep your tables in good shape.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

CIO Business Intelligence

FEBRUARY 27, 2025

Giving the mobile workforce access to this data via the cloud allows them to be productive from anywhere, fosters collaboration, and improves overall strategic decision-making. Connecting mainframe data to the cloud also has financial benefits as it leads to lower mainframe CPU costs by leveraging cloud computing for data transformations.

Metadata 88

Metadata Data Lake Cost-Benefit Forecasting 88

AWS Big Data

JUNE 10, 2024

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

Data Lake 116

Data Lake Metadata Data Warehouse Data Processing 116

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.

Data Analytics 104

Data Analytics Analytics Data Lake Data Quality 104

CIO Business Intelligence

APRIL 25, 2024

For instance, a Data Cloud-triggered flow could update an account manager in Slack when shipments in an external data lake are marked as delayed. Sharing Customer 360 insights back without data replication.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

IBM Big Data Hub

JUNE 26, 2020

Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. Yet traditional ETL tools support only a limited number of delivery styles and involve a significant amount of hand-coding.

Data Integration 107

Data Integration Data Lake Machine Learning Enterprise 107

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 98

Data Lake Analytics Snapshot Data Quality 98

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management.

Management 324

Management Data Warehouse Data Quality Data Integration 324

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.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

AWS Big Data

JANUARY 15, 2025

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. While real-time data is processed by other applications, this setup maintains high-performance analytics without the expense of continuous processing.

IoT 111

IoT Machine Learning Metadata Data-driven 111

DataKitchen

JANUARY 25, 2022

DataOps improves the robustness, transparency and efficiency of data workflows through automation. For example, DataOps can be used to automate data integration. Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake.

Consulting 244

Consulting Testing Data Quality Data Lake 244

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. Apache Hudi connector for AWS Glue For this post, we use AWS Glue 4.0,

Data Lake 98

Data Lake Visualization Dashboards Insurance 98

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.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

CIO Business Intelligence

OCTOBER 9, 2024

How will organizations wield AI to seize greater opportunities, engage employees, and drive secure access without compromising data integrity and compliance? While it may sound simplistic, the first step towards managing high-quality data and right-sizing AI is defining the GenAI use cases for your business.

Strategy 143

Strategy Modeling Management Data Lake 143

AWS Big Data

JANUARY 26, 2023

AWS Glue is a serverless, scalable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources. AWS Glue provides an extensible architecture that enables users with different data processing use cases.

Data Lake 136

Data Lake Big Data Software Interactive 136

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

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.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

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.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

Data Virtualization

NOVEMBER 3, 2022

In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of. The post Is Data Virtualization the Secret Behind Operationalizing Data Lakes?

Data Lake 52

Data Lake Big Data Data Integration Management 52

David Menninger's Analyst Perspectives

JUNE 12, 2019

Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.

Management 270

Management Data Quality Data Integration Data Lake 270

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

Data Virtualization

OCTOBER 5, 2022

For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

Data Lake 52

Data Lake Data Architecture Data Integration Management 52

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 122

Data Lake Cost-Benefit Data-driven Data Warehouse 122

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. From enhancing data lakes to empowering AI-driven analytics, AWS unveiled new tools and services that are set to shape the future of data and analytics.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

AWS Big Data

JANUARY 9, 2025

These features allow efficient data corrections, gap-filling in time series, and historical data updates without disrupting ongoing analyses or compromising data integrity. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

AWS Big Data

AUGUST 22, 2024

The infrastructure provides an analytics experience to hundreds of in-house analysts, data scientists, and student-facing frontend specialists. The data engineering team is on a mission to modernize its data integration platform to be agile, adaptive, and straightforward to use.

Data Warehouse 116

Data Warehouse Data Lake Data Integration Management 116

AWS Big Data

NOVEMBER 11, 2024

Sesha Sanjana Mylavarapu is an Associate Data Lake Consultant at AWS Professional Services. She specializes in cloud-based data management and collaborates with enterprise clients to design and implement scalable data lakes.

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Snapshot Strategy Dashboards Data Lake 111