Remove Data Processing Remove Digital Transformation Remove Metadata Remove Visualization
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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

The Data Catalog provides metadata that allows analytics applications using Athena to find, read, and process the location data stored in Amazon S3. Visual layouts in some screenshots in this post may look different than those on your AWS Management Console. Choose Run. You’re now ready to query the tables using Athena.

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Ingest and analyze your data using Amazon OpenSearch Service with Amazon OpenSearch Ingestion

AWS Big Data

A common use case that we see amongst customers is to search and visualize data. In this post, we show how to ingest CSV files from Amazon Simple Storage Service (Amazon S3) into Amazon OpenSearch Service using the Amazon OpenSearch Ingestion feature and visualize the ingested data using OpenSearch Dashboards.

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6 benefits of data lineage for financial services

IBM Big Data Hub

Download the Gartner® Market Guide for Active Metadata Management 1. Data lineage helps you answer these questions by creating highly detailed visualizations of your data flows. Efficient cloud migrations McKinsey predicts that $8 out of every $10 for IT hosting will go toward the cloud by 2024.

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What Is Cloud Data Security?

Laminar Security

Amidst these innovations, many businesses struggle to align their data security practices with the speed of digital transformation. Cloud data security is a challenge every business should tackle during their digital transformation journey. We only use your metadata for further analysis and reporting.

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Exploring the AI and data capabilities of watsonx

IBM Big Data Hub

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

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PODCAST: Making AI Real – Episode 4: Unlocking the Value of Enterprise AI with Data Engineering Capabilities

bridgei2i

In this episode of the AI to Impact Podcast, host Pavan Kumar speaks to Prinkan Pal about the evolution of data engineering and ML-operations from a closed team into a tech consulting unit. I’m your host – Pawan Kumar. Episode 4: Unlocking the Value of Enterprise AI with Data Engineering Capabilities. Pavan: Great, Prinkan.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets. smava decided to use Tableau for business intelligence, data visualization, and further analytics.