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The Syntax, Semantics, and Pragmatics Gap in Data Quality Validation Testing 

DataKitchen

The Syntax, Semantics, and Pragmatics Gap in Data Quality Validate Testing Data Teams often have too many things on their ‘to-do’ list. Syntax-Based Profiling and Testing : By profiling the columns of data in a table, you can look at values in a column to understand and craft rules about what is allowed for a column.

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Penetration testing methodologies and standards

IBM Big Data Hub

To mitigate and prepare for such risks, penetration testing is a necessary step in finding security vulnerabilities that an attacker might use. What is penetration testing? A penetration test , or “pen test,” is a security test that is run to mock a cyberattack in action.

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Apache Iceberg optimization: Solving the small files problem in Amazon EMR

AWS Big Data

Systems of this nature generate a huge number of small objects and need attention to compact them to a more optimal size for faster reading, such as 128 MB, 256 MB, or 512 MB. For more information on streaming applications on AWS, refer to Real-time Data Streaming and Analytics. with Spark 3.3.2, and JupyterEnterpriseGateway 2.6.0.

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Speed up queries with the cost-based optimizer in Amazon Athena

AWS Big Data

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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Optimizing PCI compliance in financial institutions

CIO Business Intelligence

All requirements across all domains of the PCI DSS are accounted for and tested with the teams that can remediate in case of a deviation in compliance. A Common Controls Assessment offers an invaluable tool to optimize compliance efforts across various lines of business and to the internal service providers of security patterns alike.

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Optimizing Hive on Tez Performance

Cloudera

During performance testing, evaluate and validate configuration parameters and any SQL modifications. It is advisable to make one change at a time during performance testing of the workload, and would be best to assess the impact of tuning changes in your development and QA environments before using them in production environments.

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Scale AWS Glue jobs by optimizing IP address consumption and expanding network capacity using a private NAT gateway

AWS Big Data

In this post, we will discuss two strategies to scale AWS Glue jobs: Optimizing the IP address consumption by right-sizing Data Processing Units (DPUs), using the Auto Scaling feature of AWS Glue, and fine-tuning of the jobs. Now let us look at the first solution that explains optimizing the AWS Glue IP address consumption.