Remove Big Data Remove Data Models Remove Data Profiling
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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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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

An integrated model factory to develop, deploy, and monitor models in one place using your preferred tools and languages. Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. Can you render audio/video?

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Capital One’s data-centric solutions to banking business challenges

Snorkel AI

Compute, big data, large commoditized models—all important stages. But now we’re entering a period where data investments have massive returns from all performance as well as business impact. Model-ready data refers to a feature library. It is essentially a Python library. You can pip install it.

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Capital One’s data-centric solutions to banking business challenges

Snorkel AI

Compute, big data, large commoditized models—all important stages. But now we’re entering a period where data investments have massive returns from all performance as well as business impact. Model-ready data refers to a feature library. It is essentially a Python library. You can pip install it.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

If you will ask data professionals about what is the most challenging part of their day to day work, you will likely discover their concerns around managing different aspects of data before they get to graduate to the data modeling stage. How frequently you would require to transfer the data is also of key interest.