{"id":18972,"date":"2022-10-25T10:59:45","date_gmt":"2022-10-25T08:59:45","guid":{"rendered":"https:\/\/careerfoundry.inbearbeitung.de\/en\/?p=18972"},"modified":"2023-05-11T20:50:31","modified_gmt":"2023-05-11T18:50:31","slug":"what-is-data-mining","status":"publish","type":"post","link":"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-is-data-mining\/","title":{"rendered":"What Is Data Mining?"},"content":{"rendered":"

Every business needs a wealth of data to be successful in the modern market. They need to collect, analyze, and understand data about their target audiences, the broader economic market, and even their performance to make wise decisions, avoid pitfalls, and bring in more revenue.<\/span><\/p>\n

But <\/span>collecting raw data<\/span><\/a>, even in staggeringly large amounts, is not enough. Instead, that data has to be transformed into useful information through a process called data mining.<\/span><\/p>\n

Data mining is a distinct process that turns raw data points into informative ones. Data mining involves finding different patterns, correlations, or anomalies within big data sets to predict outcomes or better understand the source of said data points.\u00a0<\/span><\/p>\n

Let\u2019s take a closer look at data mining, how it works, and how companies perform it every day. <\/span>If you\u2019d like to skip to a particular topic area, simply use the following clickable menu:<\/span><\/p>\n

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  1. How does data mining work?<\/span><\/a><\/li>\n
  2. The data mining process<\/span><\/a><\/li>\n
  3. Data mining techniques<\/span><\/a><\/li>\n
  4. Data mining applications<\/span><\/a><\/li>\n
  5. Advantages of data mining<\/span><\/a><\/li>\n
  6. Disadvantages of data mining<\/span><\/a><\/li>\n
  7. Data mining examples<\/span><\/a><\/li>\n
  8. Data mining tools<\/span><\/a><\/li>\n
  9. Summary<\/span><\/a><\/li>\n<\/ol>\n

    Ready to learn more about data mining? Let\u2019s get started!<\/span><\/p>\n

    1. How does data mining work?<\/span><\/h2>\n

    Data mining is when data analysts or scientists:<\/span><\/p>\n