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What exactly is Data Profiling: It’s Examples & Types

Pickl AI

Accordingly, the need for Data Profiling in ETL becomes important for ensuring higher data quality as per business requirements. The following blog will provide you with complete information and in-depth understanding on what is data profiling and its benefits and the various tools used in the method.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

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Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance

Alation

Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Reduce data duplication and fragmentation.

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Unlocking the 12 Ways to Improve Data Quality

Pickl AI

Implement Data Validation Rules To maintain data integrity, establish strict validation rules. This ensures that the data entered meets predefined criteria. Implementing validation rules helps prevent incorrect or incomplete data from being added to your databases.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

This is a difficult decision at the onset, as the volume of data is a factor of time and keeps varying with time, but an initial estimate can be quickly gauged by analyzing this aspect by running a pilot. Also, the industry best practices suggest performing a quick data profiling to understand the data growth.

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What Orchestration Tools Help Data Engineers in Snowflake

phData

They offer a range of features and integrations, so the choice depends on factors like the complexity of your data pipeline, requirements for connections to other services, user interface, and compatibility with any ETL software already in use. Include tasks to ensure data integrity, accuracy, and consistency.