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25 Terms All Data Analysts Must Know

  •  English    10     Public
    Source: https://careerfoundry.com/en/blog/data-analytics/25-terms-all-aspiring-data-analysts-must-know/
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  • Data analysts use a data visualization tool, commonly known as a _______, to convert all the data they receive into charts and graphs.
    Dashboard
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  • A rather broad term to describe the actual act of collecting data. Data is collected via numerous methods, depending on the nature of the business or organization.
    Data collection
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  • Data analysts should have at least a rudimentary understanding of _______, since they often play a part in the analyzing of data. It’s important to know the difference between discrete variables and continuous ones, for example.
    Statistics
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  • These are used to map out the ways in which data needs to flow. Using text and symbols, the relationships between complex streams of data and their movements can be understood at a more basic level.
    Data modelling
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  • This is a fairly simple concept. The data you gather and record must be correct, otherwise business decisions are going to be made based on false information.
    Data accuracy
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  • This is at the heart of data analytics—broadly speaking, it refers to the whole process of searching through data to identify patterns and trends. Data analysts operate at the coalface of the information industry.
    Data mining
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  • Data analysts are expected to routinely check the gathering and storage of data to ensure it meets standards of quality and formatting. Good ________ practices will save a business time and money.
    Data monitoring
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  • This is the act of removing data that will lead to distorted or inaccurate analysis. If your data is dirty, either because you’ve collected it in a poor way, or because it contains inaccuracies, then it’s time to put on a wash.
    Data cleaning / data cleansing
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  • This involves using data to make assumptions and predictions on future outcomes. It’s essential to use this to maintain a competitive advantage in business.
    Predictive analysis/predictive modelling
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  • This is the maintenance and protection of data over its entire lifecycle. It relates to security, backing up and removing duplicate data.
    Data integrity
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