data mining is not a business intelligence application

The output of a data mining task is a data pattern Is responsible for developing models, explanations, testing and proposing hypotheses using analytical methods Is responsible for extracting and discovering meaningful patterns and structure in the data The job profile involves preparation of raw data, its cleansing, transformation and modeling and finally its presentation in the form of chart/non-chart-based visualizations. It is also known as Knowledge discovery in databasesĭata Analysis is of several types – exploratory, descriptive, text analytics, predictive analysis, data mining etc.ĭata Mining specialist usually builds algorithms to identify meaningful structure in the data.Ī data mining specialist is still a Data Analyst with extensive knowledge of inductive learning and hands-on codingĪ Data Analyst usually cannot be a single person. It requires the knowledge of computer science, statistics, mathematics, subject knowledge, AI/Machine Learning It involves the intersection of machine learning, statistics, and databases. It is the process of ordering and organizing raw data in order to determine useful insights and decisions. It is the process of extracting a specific pattern from large datasets Given below is the comparison table between Data Mining and Data Analysis. Data mining generally doesn’t involve visualization tool, Data Analysis is always accompanied by visualization of results.ĭata Mining and Data Analysis Comparison Table.While Data mining is based on Mathematical and scientific methods to identify patterns or trends, Data Analysis uses business intelligence and analytics models.On the other hand, Data Analysis tests a given hypothesis. Data Mining doesn’t need any preconceived hypothesis to identify the pattern or trend in the data.The goal of Data Mining is to make data more usable while the Data Analysis helps in proving a hypothesis or taking business decisions.Data Analysis can be done on both structured, semi-structured or unstructured data. Data Mining studies are mostly on structured data.

Both are sometimes included as a subset of Business Intelligence. Data Analysis is a complete set of activities which takes care of the collection, preparation, and modeling of data for extracting meaningful insights or knowledge. Data mining is one of the activities in Data Analysis.Data Analysis gives insights or tests hypothesis or model from a dataset. Data mining identifies and discovers a hidden pattern in large datasets.To establish their unique identities, we are highlighting the major difference between them are as follows: This also depends on the organization or project team undertaking such tasks where this distinction is not marked specifically. Key Differences Between Data Mining and Data Analysisĭata Mining and Data Analysis are two distinct names and processes yet there are some views where people use them interchangeably.

Data mining is not a business intelligence application