Definition of Data Mining
Data mining is known in many ways: data mining, business intelligence, following big data. Data Mining functionality increasing margins and achieving more effective marketing campaigns is in the data.
These names are chosen Depends Data Mining The area in which it is used Big data seems now more fashionable.
Data Mining Companies are constantly Looking for a competitive advantage, something that Functionality services at a lower cost, of higher quality, and a higher speed than their competitors. The following starting point of this process is the quality and volume of data collected.
However, the data does not provide answers on its own; Without a means of interacting with them and drawing meaningful conclusions, they can be said to of no use.
Which of the following is Not a Data Mining Functionality
Data mining functionalities are used to specify the kind of patterns to be found in data mining tasks. Data mining tasks can be classified into two categories: descriptive and predictive. Descriptive mining tasks characterize the general properties of the data in the database.
Which of the following is not a data mining functionality?
A. characterization and discrimination
B. classification and regression
C. selection and interpretation
D. clustering and analysis
Answer» C. selection and interpretation
Which of the following is Not Data Mining or Data Mining for Data Organization
Data Mining, although the idea may seem like a very recent technological innovation, Following reality, this term appeared in the sixties together with other concepts such as data fishing our data archaeology.
Unlike most EHR consulting companies, we offer a team of dedicated and expert EMR clinical implementation consultants who have years of experience in the healthcare IT field.
Data mining Functionality arose with the intention or adjective of helping to understand a considerable amount of data. Although, Data Mining Functionality Could be use to draw conclusions to contribute to the improvement and growth of companies, especially with sales or customer loyalty.
Which of the following Data Mining analysis, Miners or Data Explorers must carry out Four Different Steps:
Determination Objectives of Data Mining: The client determines which purposes he wants to achieve thanks to Data Mining.
Data Mining process: Selection, cleaning, enrichment, reduction, and transformation of the database.
Determination of the Data Mining Model: First, a statistical analysis of the data must made, and then a graphic display.
Analysis of the results Data Mining: This step should verify if the results obtained are consistent.
Following Differences between Data Mining and Big Data Technology
Data mining is a Big Data Technology that has the ability to capture, manage and process all kinds of data truthfully, using tools or software that identify common patterns. These patterns could be specific characteristics, For example: consumers, generation of parameters, metrics, and many more.
Procedure of Data Mining
Data mining is the process of learning actionable information from large data sets. Use mathematical analysis to deduce the patterns and trends in the data. Traditional data exploration cannot detect these patterns because the relationships are too complex or too much data.
Data mining Generating a model is part of a more extensive process that ranges from asking questions about the data and creating a model to answer them to implementing the model in a work environment. The following six basic steps can define this process:
Define the problem
Explore the data
Design of models
Model examination and validation
Deploy and update the models