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Choosing A Graph Data Model to Best Serve Your Use Case

Ontotext

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

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Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

AWS Big Data

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

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Data Preparation and Data Mapping: The Glue Between Data Management and Data Governance to Accelerate Insights and Reduce Risks

erwin

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

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How Infomedia built a serverless data pipeline with change data capture using AWS Glue and Apache Hudi

AWS Big Data

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

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How healthcare organizations can analyze and create insights using price transparency data

AWS Big Data

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The serverless architecture features auto scaling, high availability, and a pay-as-you-go billing model to increase agility and optimize costs.

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

AWS Big Data

This data is then used by various applications for streaming analytics, business intelligence, and reporting. Amazon SageMaker is used to build, train, and deploy a range of ML models. This ensures that the data is suitable for training purposes. Additionally, SageMaker training jobs are employed for training the models.

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Addressing the Three Scalability Challenges in Modern Data Platforms

Cloudera

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. As a result, alternative data integration technologies (e.g.,