Does More Data Mean More Effective Control Charts The Surprising Truth

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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OTHER ON-DEMAND WEBINARS

Addressing Big Data Challenge Hadoop way

Xoriant Corporation

Are you unsure of how to leverage Big Data and select among the many technologies surrounding it? Don't worry - you aren't alone. Here and watch this video to know how you can address the Big Data challenges using Hadoop.
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Getting Exec Buy-In on Data Analytics

Unleashing the power of data analytics helps organizations maximize efficiency, uncover actionable insights, and drive business value. However, getting executives on board comes with its own set of challenges. So, how do you sell data analytics to the c-suite to become a more data-driven organization and leverage the power of data strategically? Join our webinar as Pragmatic Institute’s data instructors, Marilyn Coleman and Dr. Susan Gracia, discuss strategies and initiatives that will help you get and keep executive buy-in.
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New Year’s Resolutions for your Data Management Strategy

Idera

As 2019 begins, it’s a good time to assess what you accomplished last year and what goals to set for the new year. It’s also a great opportunity to review, evaluate, and update your company’s Data Management Strategy to promote alignment and derive maximum value for the business. IDERA’s Ron Huizenga will discuss data architecture and governance considerations that should be incorporated into your Data Management Strategy and Program.
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DataOps and Cloud Data Ecosystems: Overcoming the 3 Biggest Hurdles

The cloud is changing the way we use data and at the same time, the way we use data is changing the cloud. Organizations are adopting multiple cloud data platforms to maximize data’s value, but in doing so are often increasing complexity for data engineering and DataOps teams that may stifle the very reason for investing in those platforms.
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