Remove Data Processing Remove Metadata Remove Structured Data Remove Visualization
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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

AWS Glue crawls both S3 bucket paths, populates the AWS Glue database tables based on the inferred schemas, and makes the data available to other analytics applications through the AWS Glue Data Catalog. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

Admittedly, it’s still pretty difficult to visualize this difference. Additionally, it is vital to be able to execute computing operations on the 1000+ PB within a multi-parallel processing distributed system, considering that the data remains dynamic, constantly undergoing updates, deletions, movements, and growth.

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

These tools will allow them to effectively and efficiently handle extremely large volumes of disparate data – digitized histopathology slides from the visual and textual content of patient’s records, medical publications, diagnoses, etc. Behind the scenes of linking histopathology data and building a knowledge graph out of it.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. 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.