Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. These advanced data catalogs can speed the process and discover relationships and entities impossible with manual methods.

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Tableau

SEPTEMBER 23, 2021

If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.

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Alation

FEBRUARY 13, 2020

Important evaluation features include capabilities to preview a dataset, see all associated metadata, see user ratings, read user reviews and curator annotations, and view data quality information. Benefits of a Data Catalog. Improved data efficiency. Improved data context. Improved data analysis.

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Data Lakes Data Analysis Data Analysis Big Data 64

Tableau

SEPTEMBER 23, 2021

If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.

Data Governance 79

Data Governance Analytics Analytics Tableau 79

Pickl AI

JULY 19, 2023

By maintaining clean and reliable data, businesses can avoid costly mistakes, enhance operational efficiency, and gain a competitive edge in their respective industries. Best Data Hygiene Tools & Software Trifacta Wrangler Pros: User-friendly interface with drag-and-drop functionality. Provides real-time data monitoring and alerts.

Data Quality 40

Data Quality Data Profiling Data Governance Data Preparation 40

AWS Machine Learning Blog

NOVEMBER 16, 2023

Data Management – Efficient data management is crucial for AI/ML platforms. Regulations in the healthcare industry call for especially rigorous data governance. It should include features like data versioning, data lineage, data governance, and data quality assurance to ensure accurate and reliable results.

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Dataversity

MAY 3, 2021

The data value chain goes all the way from data capture and collection to reporting and sharing of information and actionable insights. As data doesn’t differentiate between industries, different sectors go through the same stages to gain value from it. Click to learn more about author Helena Schwenk.

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Data Preparation Data Quality Data Governance Cloud Data 78

Data Science Dojo

JANUARY 12, 2023

Users: data scientists vs business professionals People who are not used to working with raw data frequently find it challenging to explore data lakes. To comprehend and transform raw, unstructured data for any specific business use, it typically takes a data scientist and specialized tools.

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Data Lakes Data Warehouse Hadoop Machine Learning 221

Alation

SEPTEMBER 23, 2021

The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset. It offers a broad range of data intelligence solutions, including analytics, data governance, privacy, and cloud transformation. Data Catalog by Type.

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Data Preparation SQL Data Governance Data Analysis 52

The MLOps Blog

JUNE 27, 2023

See also Thoughtworks’s guide to Evaluating MLOps Platforms End-to-end MLOps platforms End-to-end MLOps platforms provide a unified ecosystem that streamlines the entire ML workflow, from data preparation and model development to deployment and monitoring. Data monitoring tools help monitor the quality of the data.

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Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

AUGUST 21, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. We are happy to announce that SageMaker Data Wrangler now supports using Lake Formation with Amazon EMR to provide this fine-grained data access restriction.

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AWS Data Lakes Clustering Data Preparation 83

Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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Machine Learning Machine Learning Natural Language Processing Data Preparation 78

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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AWS Machine Learning Blog

APRIL 26, 2023

Ensuring data quality, governance, and security may slow down or stall ML projects. Conduct exploratory analysis and data preparation. Monitoring setup (model, data drift). Data Engineering Explore using feature store for future ML use cases. Determine the ML algorithm, if known or possible.

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