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  2. Entry-level job - Wikipedia

    en.wikipedia.org/wiki/Entry-level_job

    An entry-level job is a job that is normally designed or designated for recent graduates of a given discipline and typically does not require prior experience in the field or profession. These roles may require some on-site training. Many entry-level jobs are part-time and do not include employee benefits.

  3. Chief analytics officer - Wikipedia

    en.wikipedia.org/wiki/Chief_analytics_officer

    A similar position is that of the chief data officer (CDO); while the CDO focuses on data processing and maintenance, the CAO focuses on providing input into operational decisions on the basis of the analysis. As such, the CAO requires experience in statistical analysis and marketing, finance, or operations.

  4. 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 and statistical methods ...

  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 analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.

  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.