AWS Big Data

DECEMBER 4, 2024

SageMaker brings together widely adopted AWS ML and analytics capabilities—virtually all of the components you need for data exploration, preparation, and integration; petabyte-scale big data processing; fast SQL analytics; model development and training; governance; and generative AI development.

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AWS Big Data

JANUARY 6, 2025

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. He has helped customers build scalable data warehousing and big data solutions for over 16 years.

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AWS Big Data

SEPTEMBER 11, 2024

This post describes how HPE Aruba automated their Supply Chain management pipeline, and re-architected and deployed their data solution by adopting a modern data architecture on AWS. The following diagram illustrates the solution architecture.

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AWS Big Data

MAY 30, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Solution overview Amazon Redshift is an industry-leading cloud data warehouse.

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AWS Big Data

NOVEMBER 26, 2024

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. For more examples and references to other posts on using XTable on AWS, refer to the following GitHub repository.

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AWS Big Data

FEBRUARY 26, 2025

The Gartner Magic Quadrant evaluates 20 data integration tool vendors based on two axesAbility to Execute and Completeness of Vision. Discover, prepare, and integrate all your data at any scale AWS Glue is a fully managed, serverless data integration service that simplifies data preparation and transformation across diverse data sources.

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AWS Big Data

DECEMBER 12, 2024

Satori enables both just-in-time and self-service access to data. Solution overview Satori creates a transparent layer providing visibility and control capabilities that is deployed in front of your existing Redshift data warehouse. The following diagram illustrates the solution architecture.

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CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

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AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

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AWS Big Data

JANUARY 15, 2025

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

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AWS Big Data

JUNE 29, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

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IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

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AWS Big Data

DECEMBER 4, 2024

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.

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IBM Big Data Hub

JANUARY 5, 2023

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. Modeling Your Data for Performance. Data architecture. The data landscape has changed significantly over the last two decades.

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AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

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AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Nasdaq’s massive data growth meant they needed to evolve their data architecture to keep up.

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CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

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AWS Big Data

APRIL 17, 2024

The AaaS model accelerates data-driven decision-making through advanced analytics, enabling organizations to swiftly adapt to changing market trends and make informed strategic choices. times better price-performance than other cloud data warehouses. Data processing jobs enrich the data in Amazon Redshift.

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AWS Big Data

JANUARY 24, 2023

In his spare time, he loves reading and finds areas for home automation Raza Hafeez is a Senior Data Architect within the Shared Delivery Practice of AWS Professional Services. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

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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. Andries has over 20 years of experience in the field of data and analytics.

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AWS Big Data

JULY 2, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools.

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AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

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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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CIO Business Intelligence

NOVEMBER 28, 2023

But at the other end of the attention spectrum is data management, which all too frequently is perceived as being boring, tedious, the work of clerks and admins, and ridiculously expensive. Still, to truly create lasting value with data, organizations must develop data management mastery. And here is the gotcha piece about data.

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AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud.

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AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Cloudera

FEBRUARY 7, 2019

With the right technology now in place, ATB Financial is landing and curating more data than ever to bring data-driven insights to the business and its customers. Implementing a Modern Data Architecture. ATB Financial is also the first to use SAS Viya to interface between SAS tools and HDP. Check out our customer stories.

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CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

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Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. AWS Glue 5.0 Finally, AWS Glue 5.0

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CIO Business Intelligence

SEPTEMBER 14, 2023

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.

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AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

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AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

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CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

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