Mad Devs’ #15 Newsletter. July 2023

What incident management metrics are, how supervised learning works, and our new expanded services in the July recap!

Mad Devs
Mad Devs — блог об IT
3 min readAug 25, 2023

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Mad Devs 15 Newsletter — July 2023

Incident Management Metrics Guide

If you want to improve the reliability of your systems, then you need to track incident management metrics. These metrics can help you measure the reliability of your plans and products, identify areas for improvement, and make data-driven decisions.

This article discusses four key incident management metrics: MTBF, MTTR, MTTA, and MTTF. We will explain how these metrics are calculated and applied and provide real-world examples of how they have been used to improve incident response.

Incident Management Metrics Guide

Semi-Supervised Learning

Artificial intelligence has made remarkable progress, resembling the futuristic depictions of science fiction writers. At the core of these great capabilities lie diverse machine learning algorithms, each adept at processing data based on their unique training models.

In this article, we delve into the fascinating world of semi-supervised learning. We explore its inner workings, the problems it addresses, and the opportunities it unlocks. Before delving into the specifics, we need briefly revisit the distinctions between supervised and unsupervised learning.

Semi-Supervised Learning

Top Data Quality Management Tools

Today, data plays a crucial role in shaping organizations’ decisions, driving their business strategies, and enhancing customer experiences. However, data’s ever-growing volume, speed, and diversity create challenges in ensuring its accuracy and dependability. This is where data quality management comes into the picture, providing structured processes and tools to evaluate, enhance, and maintain data quality throughout its entire lifecycle. This encompasses various activities, such as data validation, profiling, cleansing, enrichment, and governance.

Within this article, we will delve into the significance of data quality management and explore the methods and tools it employs. By giving priority to data quality, organizations can gain a competitive edge, make well-informed decisions, and enhance overall business outcomes, thereby unlocking the full potential of their valuable data assets. Emphasizing data quality is a strategic move that empowers businesses to leverage data in today’s data-driven world effectively.

Top Data Quality Management Tools

Discover our expanded services

Get world-class custom software development services from Mad Devs. Make your product smooth and efficient with top-reliable, highly scalable, tailored tech solutions.

Custom Software Development Services by Mad Devs

Attract, retain, and develop talented employees with HR consulting services for your tech company. Our specialists provide expertise to improve HR procedures and implement transparent work processes.

HR Consulting Services for Tech Company

Mad Devs’ trusted sources

McKinsey: In the face of volatility, CFOs and their organizations adapt

McKinsey’s newest survey of CFOs finds that finance leaders plan to keep their organizations moving forward despite their growing concern over volatility and inflation.

Managing Risk for the Next Wave of Digital Currencies

The digital currency marketplace has been in turmoil since the current “crypto winter” began in mid-2022. Holdings have been breached, fraudulent and illicit schemes have been revealed, and digital currency offerings have lost value, making the risks more evident.

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