AWS Big Data

NOVEMBER 17, 2023

Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. Let’s discuss some of the cost-based optimization techniques that contributed to improved query performance.

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AWS Big Data

FEBRUARY 1, 2023

To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. S3 bucket as landing zone We used an S3 bucket as the immediate landing zone of the extracted data, which is further processed and optimized.

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Rita Sallam

APRIL 2, 2023

Are there mitigation strategies that show reasons for optimism? Are there mitigation strategies that can be implemented successfully that could provide policy guidance and reasons for optimism in the face of ever increasing frequency of extreme weather events? Here is the link to Tellius’s Show Floor Showdown video.

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AWS Big Data

JANUARY 24, 2024

More data files leads to more metadata stored in manifest files, and small data files often cause an unnecessary amount of metadata, resulting in less efficient queries and higher Amazon S3 access costs. The output will give a count of the number of data and metadata files deleted.

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Ontotext

FEBRUARY 23, 2023

The engines must facilitate the advanced data integration and metadata data management scenarios where an EKG is used for data fabrics or otherwise serves as a data hub between diverse data and content management systems. Enterprise knowledge graphs (EKG) require graph databases, which serve multiple purposes. This era is over! billion edges.

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Octopai

JANUARY 19, 2021

Octopai can fully map the BI landscape and trace metadata movement in a mixed environment including complex multi-vendor landscapes. About Octopai: Octopai was founded in 2015 by BI professionals who realized the need for dynamic solutions in a stagnant market.

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Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. For details, see their SIGMOD 2015 paper where Michael Armbrust & co.

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