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  2. Troubleshooting - Wikipedia

    en.wikipedia.org/wiki/Troubleshooting

    Troubleshooting is a form of problem solving, often applied to repair failed products or processes on a machine or a system. It is a logical, systematic search for the source of a problem in order to solve it, and make the product or process operational again. Troubleshooting is needed to identify the symptoms.

  3. Microsoft Power BI - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Power_BI

    Microsoft Power BI is an interactive data visualization software product developed by Microsoft with a primary focus on business intelligence (BI). [7] It is part of the Microsoft Power Platform . Power BI is a collection of software services, apps, and connectors that work together to turn various sources of data into static and interactive ...

  4. Microsoft Dynamics 365 - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Dynamics_365

    Microsoft Dynamics 365 is an integrated suite of enterprise resource planning (ERP) and customer relationship management (CRM) applications offered by Microsoft. [1] Combines various functions such as sales, customer service, field service, operations, finance, marketing, and project service automation into a single platform.

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    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  6. Seven basic tools of quality - Wikipedia

    en.wikipedia.org/wiki/Seven_Basic_Tools_of_Quality

    The seven basic tools of quality are a fixed set of visual exercises identified as being most helpful in troubleshooting issues related to quality. [1] They are called basic because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.

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  9. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is an interdisciplinary field [10] focused on extracting knowledge from typically large data sets and applying the knowledge from that data to solve problems in other application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, and summarizing

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