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Differentiating Data Mining & Data Analysis
The outbreak of Big Data & Data Science revolution has given rise to several benefits as a part of our daily lives & business applications. Businesses across various sectors are relying heavily on the insights from Big Data to make strategically accurate smart business decisions. But, how exactly are the insights from Big Data are extracted & converted into actionable insights? This is where Data Science comes into the game of play.
The data exploratory process in Data Science consists of two major aspects namely, Data Analysis & Data Mining. Both these approaches are very crucial in the process of extracting the insights from data of any format & size. So, having skills in Data Mining & Data Analysis in your inventory would be very crucial if you are willing to become a Data Science expert. Master the skills in Data Mining, Data Analysis & other essential skills in Data Science with the help of our advanced Data Science Training In Hyderabad program.
Now, let’s understand the difference between Data Mining & Data Analysis.
What Exactly Is Data Mining & Data Analysis?
Data Mining-
Data Mining can be interpreted as systemic approach that helps in identifying and uncovering hidden patterns and information encrypted inside datasets. Data Mining is also the first step in the Data exploratory process. To build expertise in Data Mining, you need to develop skills in Machine Learning, Statistics & Rational Databases.
Skills in coding are also very crucial for Data Mining.
Data Analysis–
Data Analysis is a multitier process that involves aspects like data extraction, data cleaning, data transforming, data modeling and data visualization. Data Mining itself is a sub process in Data Analysis. Data Analysis helps in the extracting actionable insights from Big Data & plays a key role in the decision making process. Data Analysis requires skills in Statistical Modeling, Data Modeling, & as well AI & Machine Learning techniques.
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