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The 2016 Crystal Ball – What’s Next in Data?

Alation

Considering what we’ve seen this year in industry trends and patterns, we have compiled some predictions for 2016 from our co-founders at Alation. 2016 will be the year of the “logical data warehouse.” In 2016, these will increasingly be deployed to query multiple data sources. Data sprawl has been prevalent for several years.

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Data Fabric and Address Verification Interface

IBM Data Science in Practice

The concept was first introduced back in 2016 but has gained more attention in the past few years as the amount of data has grown. IBM’s Next Generation DataStage is an ETL tool to build data pipelines and automate the effort in data cleansing, integration and preparation.

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Improving air quality with generative AI

AWS Machine Learning Blog

In this solution, we leverage the reasoning and coding abilities of LLMs for creating reusable Extract, Transform, Load (ETL), which transforms sensor data files that do not conform to a universal standard to be stored together for downstream calibration and analysis. She holds 30+ patents and has co-authored 100+ journal/conference papers.

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7 Best Machine Learning Workflow and Pipeline Orchestration Tools 2024

DagsHub

The project was created in 2014 by Airbnb and has been developed by the Apache Software Foundation since 2016. Flexibility: Its use cases are wider than just machine learning; for example, we can use it to set up ETL pipelines. This also means that it comes with a large community and comprehensive documentation.