Difference between Data Mining and Data Warehousing | MBA course in Bangalore

Posted by Prof Manoranjan H P On 16/04/2022 10:44:51

As an MBA Aspirants must know the which specialization we suppose to choose…while choosing a Business Analytics Specialization The Important Concept to Know About is  Data Mining and Data Warehousing

Data Mining in Real-world

Data mining is the process of discovering hidden patterns in data using statistical models and algorithms. Data warehousing is a similar method of data analysis, but it employs a different set of users and has a slightly different aim. To get this, think of data warehousing as the first stage of data mining. Data is collected and managed by skilled data engineers and scientists in centralized databases. These databases collect data from a variety of sources and categories it.

The following are characteristics of Data Mining.

  • It is a method for determining data patterns.
  • It is a general method for extracting meaningful info from a set of data.
  • In this method, data is analyzed multiple times.
  • It is carried out by business owners and engineers in order to extract useful information.
  • To find patterns in data, it employs a variety of approaches, including pattern recognition.
  • It aids in the detection of undesired system faults.
  • It is less expensive than other statistical data processing methods.
  • It isn't entirely correct because nothing is perfect in the actual world.

Data Warehousing In Real World

Data warehousing is the process of collecting and arranging data in a single database, whereas data mining is the process of retrieving valuable data from databases. We may conclude from the definition that the data mining process relies on the data warehouse to find patterns in data and draw meaningful conclusions.

The following are the Characteristics of Data Warehousing.

  • It's an analytics database system.
  • It collects all important information into a single module.
  • Engineers are in charge of the data warehousing process.
  • Data is stored in this format on a regular basis.
  • Data is extracted and stored in this procedure for reporting convenience.
  • It is updated on a regular basis.
  • This is why it is utilized by huge corporations to keep current.
  • It aids in the simplification of all types of corporate data.
  • If the data required for analysis is not incorporated into the data warehouse, data loss is a possibility.
  • It retains a significant amount of historical data that can be used to analyze trends and seasonality in order to produce more accurate forecasts.

Conclusion:

Both data mining and data warehousing are critical processes for preventing data fraud at all levels of a company and improving statistics and ranking. Data warehouses maintain data records and data mining techniques aid in the extraction of useful data and information in compliance with requirements. Both procedures function in combination to help any organization's management.


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