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How to Assess Data Quality Readiness for Modern Data Pipelines

Dataversity

The key to being truly data-driven is having access to accurate, complete, and reliable data. In fact, Gartner recently found that organizations believe […] The post How to Assess Data Quality Readiness for Modern Data Pipelines appeared first on DATAVERSITY.

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Improving Data Pipelines with DataOps

Dataversity

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

DataOps 59
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How to Build ETL Data Pipeline in ML

The MLOps Blog

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier. What is an ETL data pipeline in ML? Let’s look at the importance of ETL pipelines in detail.

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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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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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Why Is Data Quality Still So Hard to Achieve?

Dataversity

We exist in a diversified era of data tools up and down the stack – from storage to algorithm testing to stunning business insights.

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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data. It truly is an all-in-one data lake solution.