Does More Data Mean More Effective Control Charts The Surprising Truth

info.minitab.com

When you need to monitor and control variation in your process, a control chart will help you to separate special causes from common cause variation or random variation. Yet how do todays types of data, including full inspection, impact this tool's effectiveness?
The control chart was created in the 1920s, a time when measurement, data capture and calculation were done manually, making sampling essential. Today, how data is collected has all changed.
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Spotlight

User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

OTHER ON-DEMAND WEBINARS

Rapid Response Analytics Accelerates Analytics ROI

Health Catalyst Inc

Rapid Response Analytics (RRA), an application suite that consists of two elements: curated, modular data kits called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build populations without needing to know how to write SQL and data science code. RRA increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests. Learning Objectives: Discover how RRA is like a meal delivery kit that allows you to take components and customize them to quickly tailor and deliver meaningful insights.
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Expand Access to Credit with Alternative Data from Equifax

Equifax analysis indicates that approximately 91.5 million consumers in the US either have no credit file, or have insufficient information in the file to generate a traditional credit score. Your visibility into credit applicants determines whether you will offer more loans or miss profitable opportunities. By giving you incre
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IBM Data Science Community

As enterprises become more agile, centralization appears more and more a thing of the past waterfall world. This need is equally true with data platforms. This paradigm drove us to build a Data Mesh, this next generation of data platforms for PayPal Credit. This talk will detail quickly go over the evolution of data platforms, highlight the problems of current data platforms, and explain why we decided to build a Data Mesh. I will detail the four principles of the Data Mesh, how we got started, and describe some current and future challenges and how we plan to solve them. Part of the Expert Hour series.
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What is Anomaly Detection and its Role in Preventative Analytics

DataRPM

Equipment downtime is a multi-billion-dollar problem which will only continue to grow with exploding sensor data. According to IDC, by 2018 a third of industrial companies will be disrupted by “Industrial IoT enabled competitors.” So how can companies monetize their IoT investments for higher operational efficiencies and productivity? Anomaly Detection and Prediction is the silver bullet that companies need to maximize their machine uptime and performance. Watch the on-demand webinar featuring the Dean of Big Data, Bill Schmarzo, Chief Technology Officer, Big Data at Dell EMC and Seth Page, General Manager and Head of Partnerships at Progress DataRPM, to learn how zero factory downtime can be a reality.
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Spotlight

User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

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