Remove Big Data Remove Data Platform Remove Metadata
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Achieve your AI goals with an open data lakehouse approach

IBM Journey to AI blog

Also, a lakehouse can introduce definitional metadata to ensure clarity and consistency, which enables more trustworthy, governed data. And AI, both supervised and unsupervised machine learning, is often the best or sometimes only way to unlock these new big data insights at scale. All of this supports the use of AI.

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Search enterprise data assets using LLMs backed by knowledge graphs

Flipboard

Enterprises are facing challenges in accessing their data assets scattered across various sources because of increasing complexities in managing vast amount of data. Traditional search methods often fail to provide comprehensive and contextual results, particularly for unstructured data or complex queries.

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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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Manage access controls in generative AI-powered search applications using Amazon OpenSearch Service and Amazon Cognito

Flipboard

Solution overview By combining the powerful vector search capabilities of OpenSearch Service with the access control features provided by Amazon Cognito , this solution enables organizations to manage access controls based on custom user attributes and document metadata. If you don’t already have an AWS account, you can create one.

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How Can The Adoption of a Data Platform Simplify Data Governance For An Organization?

Pickl AI

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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18 Data Profiling Tools Every Developer Must Know

Marktechpost

As a result, it’s easier to find problems with data quality, inconsistencies, and outliers in the dataset. Metadata analysis is the first step in establishing the association, and subsequent steps involve refining the relationships between individual database variables.

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Demand forecasting at Getir built with Amazon Forecast

AWS Machine Learning Blog

Among those algorithms, deep/neural networks are more suitable for e-commerce forecasting problems as they accept item metadata features, forward-looking features for campaign and marketing activities, and – most importantly – related time series features. He loves combining open-source projects with cloud services.