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Normalize

Level

Associate

'Normalize' is like making things fit in or seem usual, usually after something new or unexpected has happened. For instance, you might normalize a new routineregularly followed procedure of cleaning your room every weekend.

'Normalize' means to make something standard, regular, or normal, especially something that was once strange or different. Like a business might try to normalize flexible work scheduleswork timings that can be changed after they've tried it for some time.

To 'normalize' is to establishmentsetting up standardization or normalcy in a system or environment, often following a situational anomalysomething different from standard or unprecedented event. It signifies transitioning an irregularity into a state of regularity or conformityagreement with standards with established norms.

Context

Business

In the creative industries, 'normalize' could refer to making something less tabooprohibited by social custom or more accepted. A creative director might express, 'We should normalize the portrayaldepict or represent something of mental health issues in our films.'

In social impact work, 'normalize' might suggest making a certain behavior or practice standard. An activistcampaigner for social change might say, 'We must normalize sustainability practicesactions supporting environment to combat climate change.'

In the business world, 'normalize' often refers to adjusting financial figures for unusual circumstances to provide a fair comparison. For instance, an auditorperson checking financial accounts might say, 'We've normalized the company's earningsmoney made to account for the unexpected expenses.'

In a technology setting, 'normalize' is often used in the context of database design, to eliminate redundancyunnecessary repetition and improve accuracy. A database architectperson who designs database structure may say, 'To normalize the database, we've removed all the duplicate entries.'

The term 'normalize' in AI often means adjusting values measured on different scales to a common scale. A data scientistprofessional dealing with large sets of data might state, 'We need to normalize the data to ensure the algorithmset of rules to solve a problem works efficiently.'

Practice in Professional Context

Listen to the given audio and respond using 'normalize'.

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