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How to Conduct User Acceptance Testing: Process Stages, Deliverables, and End-User Testing Place in Quality Assurance

Altexsoft

When conducting various quality assurance activities , development teams are able to look at the product from the user’s standpoint. What is user acceptance testing and how is it different from quality assurance? Traditionally, quality assurance engineers will be responsible for end-user feedback processing.

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Software Outsourcing: Why CEOs Love It

Gorilla Logic

Monetize data with technologies such as artificial intelligence (AI), machine learning (ML), blockchain, advanced data analytics , and more. Not surprisingly, the skill sets companies need to drive significant enterprise software builds, such as big data and analytics, cybersecurity, and AI/ML, are among the most competitive.

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A Sneak Peek into Geekle’s online events of 2024

Apiumhub

AI in Product and Business Analytics Conf – February 27. This event explores the role of AI in analyzing business and product data, offering insights into advanced analytics techniques and the use of AI for strategic decision-making. Another one of Geekle’s online events.

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Hire ETL Developer in Ukraine

Mobilunity

After combining all sources of information, the analyst will be able to qualitatively analyze the information and deliver analytical results to the business. Extracting, collecting, and analyzing big data is vital for making major business decisions. ETL troubleshooting and quality assurance.

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Data trust and the evolution of enterprise analytics in the age of AI

CIO

The foundational tenet remains the same: Untrusted data is unusable data and the risks associated with making business-critical decisions are profound whether your organization plans to make them with AI or enterprise analytics. Like most, your enterprise business decision-makers very likely make decisions informed by analytics.

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Enterprise Master Patient Index: How to Implement Patient Identity Management

Altexsoft

This robust tool is typically used to perform data governance for AI applications, business analytics, or powerful knowledge bases, all supported by a self-service data pipeline. This can be their referential matching tech or an analytical add-on Enrich. How to prepare for EMPI and maintain data quality.

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

CIO

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.