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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

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.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

Transferring ownership of data/datasets to domain-specific units that possess a deeper understanding of rules around the data empowers teams, improves data quality and trust, and greatly accelerates the building of data models and analytics. However, data mesh is not about introducing new technologies.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 1

AWS Big Data

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

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Texas Rangers data transformation modernizes stadium operations

CIO Business Intelligence

She decided to bring Resultant in to assist, starting with the firm’s strategic data assessment (SDA) framework, which evaluates a client’s data challenges in terms of people and processes, data models and structures, data architecture and platforms, visual analytics and reporting, and advanced analytics.

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Showpad accelerates data maturity to unlock innovation using Amazon QuickSight

AWS Big Data

Showpad also struggled with data quality issues in terms of consistency, ownership, and insufficient data access across its targeted user base due to a complex BI access process, licensing challenges, and insufficient education. The company also used the opportunity to reimagine its data pipeline and architecture.