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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Analysts may apply a variety of techniques, referred to as exploratory data analysis, to begin understanding the messages contained within the obtained data. [30] The process of data exploration may result in additional data cleaning or additional requests for data; thus, the initialization of the iterative phases mentioned in the lead ...

  3. Résumé - Wikipedia

    en.wikipedia.org/wiki/Résumé

    A résumé or resume (or alternatively resumé), [a] [1] is a document created and used by a person to present their background, skills, and accomplishments. Résumés can be used for a variety of reasons, but most often are used to secure new jobs, whether in the same organization or another.

  4. List of professional designations in the United States

    en.wikipedia.org/wiki/List_of_professional...

    Certified Usability Analyst: CUA Certified User Experience Analyst: CXA Google Associate Cloud Engineer ACE Lean IT Kaizen: ... Professional Practice Degrees ...

  5. 50 Professionals Share The Popular Misconceptions People Have ...

    www.aol.com/50-professionals-share-popular...

    1. “You could be an analyst.” or 2. You could be a “consultant.” Myth: There’s a category … and you could have a career doing that … Truth: Example: An analyst is not a useful ...

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    For example, a data analyst might analyze sales data to identify trends in customer behavior and make recommendations for marketing strategies. [37] Data science, on the other hand, is a more complex and iterative process that involves working with larger, more complex datasets that often require advanced computational

  7. Analytics - Wikipedia

    en.wikipedia.org/wiki/Analytics

    Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.

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