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The power of remote engine execution for ETL/ELT data pipelines

IBM Journey to AI blog

According to International Data Corporation (IDC), stored data is set to increase by 250% by 2025 , with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

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Data Fabric and Address Verification Interface

IBM Data Science in Practice

How can organizations get a holistic view of data when it’s distributed across data silos? Implementing a data fabric architecture is the answer. What is a data fabric? Ensuring high-quality data A crucial aspect of downstream consumption is data quality.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Moreover, ETL pipelines play a crucial role in breaking down data silos and establishing a single source of truth.

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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

The data universe is expected to grow exponentially with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase pressure to manage cloud costs efficiently and complicate governance of AI and data workloads.

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Using Agile Data Stacks To Enable Flexible Decision Making In Uncertain Economic Times

Precisely

This requires access to data from across business systems when they need it. Data silos and slow batch delivery of data will not do. Stale data and inconsistencies can distort the perception of what is really happening in the business leading to uncertainty and delay.

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Ensure Success with Trusted Data When Moving To The Cloud

Precisely

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. Data Integrity Is a Business Imperative As the number of data tools and platforms continues to grow, the amount of data silos within organizations grow too.

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Enable data sharing through federated learning: A policy approach for chief digital officers

AWS Machine Learning Blog

Duration of data informs on long-term variations and patterns in the dataset that would otherwise go undetected and lead to biased and ill-informed predictions. Breaking down these data silos to unite the untapped potential of the scattered data can save and transform many lives. Much of this work comes down to the data.”

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