Remove Data Lake Remove Data Processing Remove Data Quality
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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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Set up advanced rules to validate quality of multiple datasets with AWS Glue Data Quality

AWS Big Data

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. BMS’s EDLS platform hosts over 5,000 jobs and is growing at 15% YoY (year over year). About the authors Sivaprasad Mahamkali is a Senior Streaming Data Engineer at AWS Professional Services.

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Introducing the technology behind watsonx.ai, IBM’s AI and data platform for enterprise

IBM Big Data Hub

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. Data: the foundation of your foundation model Data quality matters. When objectionable data is identified, we remove it, retrain the model, and repeat.

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Accomplish Agile Business Intelligence & Analytics For Your Business

datapine

You need to determine if you are going with an on-premise or cloud-hosted strategy. You will need to continually return to your business dashboard to make sure that it’s working, the data is accurate and it’s still answering the right questions in the most effective way. Ensure the quality of production.

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Governing data in relational databases using Amazon DataZone

AWS Big Data

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

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How data literacy allows gen AI to drive productivity at Dow

CIO Business Intelligence

We also have a blended architecture of deep process capabilities in our SAP system and decision-making capabilities in our Microsoft tools, and a great base of information in our integrated data hub, or data lake, which is all Microsoft-based. That’s what we’re running our AI and our machine learning against.