Sun.Dec 17, 2023

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Analytics in Machining Techniques in Making Advanced Exoskeleton Robots

Smart Data Collective

Analytics technology has seriously disrupted the manufacturing industry over the last decade. According to Mordor Intelligence, the market for analytics in manufacturing will be worth $19.5 billion by 2028. There are a number of ways that analytics has helped manufacturing companies improve their bottom line.

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Data-Driven Decision Making: Leveraging Analytics in Process Management

Modern Analyst

The function of business analysts has changed dramatically in today's technologically-advancing, digitally transformed business environment. Using analytics for data-driven decision-making is one of the major areas where their experience is becoming more and more important, particularly in the field of process management. It clarifies how business analysts can use data to optimize workflows and lead organizations toward long-term success.

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Maximizing Project Efficiency With A Point Cloud Viewer Software

Smart Data Collective

Cloud technology has been a godsend for companies in almost every sector. Therefore, it should not be particularly surprising that a growing number of companies are investing in cloud-based tools to improve scalability and boost profits.

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Tailored financial dashboards for actionable insights

Phocas

A business planning and analytics platform allows finance teams to integrate multiple sets of data sources together to create financial statements, budgets and forecasts.

Finance 59
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Reduce Bias in Hiring: Structured Interview Questions for Employers

Structured interview questions are a valuable tool for reducing bias in hiring. They help: Ensure all candidates are asked the same questions in the same way Level the playing field so all candidates have a fair chance of being successful Improve credibility, reliability, and validity Download the guide to get the most out of your interview questions!

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Artificial Intelligence and Machine Learning in Software Development

Smart Data Collective

New technology has always transformed aspects of our lives, but perhaps none has more potential to bring change than artificial intelligence (AI) and machine learning (ML). While the latest developments are watched with excitement by some and trepidation by others, engineers must look at how best to use them.