What to Consider When Selecting a Data Engineering Solution

As a business owner or manager, you know that data is a critical component of making informed decisions and driving growth. There are many approaches to building systems for collecting, storing, and analyzing data at scale. With so many data engineering solutions available on the market, it can be overwhelming to select the right one …

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AI Data Engineering Lifecycle Checklist

Machine learning is powering most of the recent advancements in artificial intelligence including  autonomous systems, computer vision, natural language processing, predictive analytics, and a wide range of applications among the seven patterns of AI. However, in order for these systems to be able to create accurate generalizations, these machine learning systems must be trained on …

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INFOGRAPHIC: Data prep and Labeling

The market for data labeling is growing and becoming very important as more and more companies need clean, accurate, well-labeled data for ML training. In this infographic we share key stats and insights from Cognilytica’s recent Data Engineering, Preparation, and Labeling for AI 2019 report including AI’s secret, the market for data prep solutions, and …

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Data Engineering, Preparation, and Labeling for AI 2019

Document ID: CGR-DE100 | Last Updated: Jan. 31, 2019 It has always been the case that garbage in is garbage out in computing, but it is especially the case with regards to machine learning data. In this report, Cognilytica evaluates the requirements for data preparation solutions that aim to clean, augment, and otherwise enhance data …

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