Introduction to Data Mining and its Importance.
                     INTRODUCTION TO DATA 
MINING AND ITS 
IMPORTANCE
What Is Data Mining?
• Data mining is an automated process that consists of searching large datasets for 
patterns humans might not spot.
• For example, weather forecasting analyzes troves of historical data to identify 
patterns and predict future weather conditions based on time of year, climate, and 
other variables.
Source: www.springboard.com
How Does Data Mining Work?
• In the information economy, data is 
downloaded, stored, and analyzed for most 
every transaction we perform, from Google 
searches to online shopping. 
• The benefits of data mining are applicable 
across industries, from supply chains to 
healthcare, advertising, and marketing.
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Data Mining Process 
• Collection: Data is collected, organized, and 
loaded into a data warehouse. 
• Understanding: Business analysts and data 
scientists will examine the properties of the 
data.
• Preparation: Data must be cleaned, 
constructed, and formatted into the desired 
form. 
• Modeling: Modeling techniques are 
selected for the prepared dataset.
• Evaluation: The model results are evaluated 
in the context of business objectives.
Source: www.springboard.com
Data mining vs. data analysis
• Data mining is a systematic process of 
identifying and discovering hidden patterns 
and information in a large dataset. 
• Data analysis is a subset of data mining, 
which involves analyzing and visualizing 
data to derive conclusions.
Source: www.springboard.com
Data mining vs. machine learning
• Machine learning is the design, study, and 
development of algorithms that enable 
machines to learn without human 
intervention. 
• Both data mining and machine learning fall 
under the field of data science, which is 
why the two terms are often confused. 
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Data mining vs. data warehousing
• Data warehousing is a process that is used 
to integrate data from multiple sources into 
a single database. 
• Unlike data mining, data warehousing does 
not involve extracting insights from data.
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IMPORTANCE OF DATAMINING
Marketing
• Big data makes it possible to extract 
predictive insights about consumers from 
large databases, enabling businesses to 
learn more about their customers.
• Data mining is also used for market 
segmentation.
• Some businesses use predictive analytics to 
infer implicit or future customer needs.
Source: www.springboard.com
Business analytics
• Business analytics is the process of 
transforming data into business insights. 
• The focus of business analytics is on 
recognizing patterns, developing models to 
explain past events, create predictions for 
future events, and recommend actions to 
optimize business outcomes.
Source: www.springboard.com
Business intelligence
• Business intelligence (BI) transforms data into actionable insights.
• For example, a BI dashboard could show how many customers are buying a 
particular item during a promotion, or how many engagements a social media 
campaign is attracting.
Source: www.springboard.com