Remove Data Integration Remove Data Platform Remove Metadata
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Ken Claffey, CEO of VDURA – Interview Series

Unite.AI

Can you share the story behind the creation of the VDURA Data Platform and the key challenges you aimed to address in the AI and HPC landscape? The VDURA Data Platform was developed to address a critical and growing gap in data infrastructure for AI and HPC workloads: balancing high performance with enterprise-grade durability.

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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. The 18 best data profiling tools are listed below.

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Journey to AI blog

It’s often described as a way to simply increase data access, but the transition is about far more than that. When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard.

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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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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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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.

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Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

AWS Machine Learning Blog

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.