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How Can The Adoption of a Data Platform Simplify Data Governance For An Organization?

Pickl AI

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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How IBM HR leverages IBM Watson® Knowledge Catalog to improve data quality and deliver superior talent insights

IBM Journey to AI blog

A long-standing partnership between IBM Human Resources and IBM Global Chief Data Office (GCDO) aided in the recent creation of Workforce 360 (Wf360), a workforce planning solution using IBM’s Cognitive Enterprise Data Platform (CEDP). Data quality is a key component for trusted talent insights.

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Data architecture strategy for data quality

IBM Journey to AI blog

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

Some of the popular cloud-based vendors are: Hevo Data Equalum AWS DMS On the other hand, there are vendors offering on-premise data pipeline solutions and are mostly preferred by organizations dealing with highly sensitive data. Dagster Supports end-to-end data management lifecycle. It supports multiple file formats.It

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Bring your own AI using Amazon SageMaker with Salesforce Data Cloud

AWS Machine Learning Blog

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another.

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Data virtualization unifies data for seamless AI and analytics

IBM Journey to AI blog

Data integration stands as a critical first step in constructing any artificial intelligence (AI) application. While various methods exist for starting this process, organizations accelerate the application development and deployment process through data virtualization. Why choose data virtualization?

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

During a data analysis project, I encountered a significant data discrepancy that threatened the accuracy of our analysis. I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity.