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Visualize Amazon DynamoDB insights in Amazon QuickSight using the Amazon Athena DynamoDB connector and AWS Glue

AWS Big Data

These include internet-scale web and mobile applications, low-latency metadata stores, high-traffic retail websites, Internet of Things (IoT) and time series data, online gaming, and more. Athena is a serverless, interactive service that allows you to query data from a variety of sources in heterogeneous formats, with no provisioning effort.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog. You can deploy the end-to-end solution to visualize and analyze trends of the observability metrics.

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Automated Metadata Management Tools: Why Some Companies Struggle and Others Flourish During Corona

Octopai

Organizations are turning to the cloud and automated metadata management tools to successfully manage their business’s data. Hear real use cases of BI teams who are leveraging metadata management automation on the cloud while working remotely Check out our webinar "BI During COVID-19." One word for you: Cloud. Watch the Webinar.

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How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

AWS Big Data

HR&A has used Amazon Redshift Serverless and CARTO to process survey findings more efficiently and create custom interactive dashboards to facilitate understanding of the results. Figure 1: Workflow illustrating data ingesting, transformation, and visualization using Redshift and CARTO.

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Data governance in the age of generative AI

AWS Big Data

The need for an end-to-end strategy for data management and data governance at every step of the journey—from ingesting, storing, and querying data to analyzing, visualizing, and running artificial intelligence (AI) and machine learning (ML) models—continues to be of paramount importance for enterprises.

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Why Establishing Data Context is the Key to Creating Competitive Advantage

Ontotext

Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information. Without metadata management and other data-related operations with semantic technologies, organizations often struggle to connect data sets and achieve a unified view of their enterprise data.

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Data Lineage Through the Decades: Where It’s Going (And Where It’s Been)

Alation

The product collected an impressive amount of metadata, from the user interface to the database structure. It then translated all that metadata into an image resembling a spider’s web. Back then, visualizing impact analysis seemed futuristic with great promise. There was just one problem: the image was incredibly complex.