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In Uncertain Times, Data Integrity is More Important Than Ever

Precisely

Business needs and challenges 77% of respondents say data-driven decision-making is the top goal of their data programs – and they’re also looking to accelerate those processes. Those who have already made progress toward that end have used advanced analytics tools that work outside of their application-based data silos.

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Data architecture strategy for data quality

IBM Journey to AI blog

Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable. Perform data profiling (the process of examining, analyzing and creating summaries of datasets).

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How to Build ETL Data Pipeline in ML

The MLOps Blog

These pipelines assist data scientists in saving time and effort by ensuring that the data is clean, properly formatted, and ready for use in machine learning tasks. Moreover, ETL pipelines play a crucial role in breaking down data silos and establishing a single source of truth.

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HCLS Companies: 10 Data Analytics Challenges to Overcome with Sigma Computing & Snowflake

phData

See how phData created a solution for ingesting and interpreting HL7 data 4. Data Quality Inaccurate data can have negative impacts on patient interactions or loss of productivity for the business. Sigma and Snowflake offer data profiling to identify inconsistencies, errors, and duplicates.

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Common Data Governance Challenges & Their Solutions

Alation

Deeper knowledge of how data is used powers deeper understanding of the data itself. Siloed Data. Silos exist in every enterprise, and they never fail to cause data governance challenges. Silos arise for a range of reasons. Why Do Data Silos Happen? The fast pace of data collection.