Remove Data Integration Remove Measurement Remove Unstructured Data
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Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

From reactive fixes to embedded data quality Vipin Jain Breaking free from recurring data issues requires more than cleanup sprints it demands an enterprise-wide shift toward proactive, intentional design. Data quality must be embedded into how data is structured, governed, measured and operationalized.

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The success of GenAI models lies in your data management strategy

CIO Business Intelligence

How will organizations wield AI to seize greater opportunities, engage employees, and drive secure access without compromising data integrity and compliance? While it may sound simplistic, the first step towards managing high-quality data and right-sizing AI is defining the GenAI use cases for your business.

Strategy 143
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The DataOps Vendor Landscape, 2021

DataKitchen

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Azure DevOps. AWS Code Deploy.

Testing 304
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Data governance in the age of generative AI

AWS Big Data

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Because it is that important.

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Eating the Knowledge Soup, Literally

Ontotext

What lies behind building a “nest” from irregularly shaped, ambiguous and dynamic “strings” of human knowledge, in other words of unstructured data? To do that Edamam, together with Ontotext, worked to develop a knowledge graph with semantically enriched nutrition data. 450 g chicken broth, or more for thinning.