AWS Machine Learning Blog

APRIL 17, 2023

For scenarios where you need to add your own custom scripts for data transformations, you can write your transformation logic in Pandas, PySpark, PySpark SQL. With the Data Wrangler custom transform capability, you can write your transformation logic in Pandas, PySpark, PySpark SQL. After notebook files (.ipynb)

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AWS Python ML ML 98

Alation

JANUARY 25, 2022

For instance, technical power users can explore the actual data through Compose , the intelligent SQL editor. Those less familiar with SQL can search for technical terms using natural language. Automated Data Orchestration (AKA DataOps). DataOps is the leading process concept in data today. Spoiler alert!

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Alation

APRIL 4, 2023

Troubleshooting data issues , for an exploding number of disjointed systems and tools, breaks self-service for data users and creates gaps in visibility for dataOps. Building data pipelines is challenging, and complex requirements (as well as the separation of many sources) leads to a lack of trust.

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DataOps Data Engineering Data Engineering Data Engineering 52

phData

MAY 11, 2023

There are many frameworks for testing software, but the right way to test the data and SQL scripts that change data are less obvious. This is a simple example of how SQL that compiles and runs perfectly might fail when trying to migrate it to a higher environment like production. Run the create clone SQL statement.

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phData

OCTOBER 8, 2024

Throughout our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps. dbt has modularity and SQL-focused transformation that makes the logic easy to translate, the tests ensure the data is accurate, and documentation and modularity smooth the maintenance.

DataOps 52

DataOps Data Modeling Data Models SQL 52

phData

OCTOBER 16, 2023

Throughout our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps. dbt has modularity and SQL-focused transformation that makes the logic easy to translate, the tests ensure the data is accurate, and documentation and modularity smooth the maintenance.

DataOps 52

DataOps Data Modeling Data Models SQL 52

Alation

MAY 24, 2022

Peter: One common challenge that we see across our customer base is that currently much of this data quality information is siloed within IT , data engineering , or dataOps. Talo: Who benefits from this initiative?

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Data Quality Data Pipeline DataOps Analytics 52