Data Mining

Data mining

_____ is extracting information, looking for hidden, valid, and potentially useful patterns in huge data sets.

Data Mining

_____ is all about discovering unsuspected/ previously unknown relationships amongst the data

Data Mining

It is a multi-disciplinary skill that uses machine learning, statistics, AI and database technology.

Knowledge discovery, Knowledge extraction, Knowledge extraction, information harvesting

Data mining is also called as _____, _____, ______, ______, etc.

Communication

Data mining techniques are used in _____sector to predict customer behavior to offer highly targetted and relevant campaigns

Insurance

Data mining helps _____companies to price their products profitable and promote new offers to their new or existing customers

Education

Data mining benefits educators to access student data, predict achievement levels and find students or groups of students which need extra attention

Manufacturing

With the help of Data Mining _____ can predict wear and tear of production assets. They can anticipate maintenance which helps them reduce them to minimize downtime

Banking

Data mining helps finance sector to get a view of market risks and manage regulatory compliance.

Retail

Data Mining techniques help ____ malls and grocery stores identify and arrange most sellable items in the most attentive positions.

Service providers

_____ like mobile phone and utility industries use Data Mining to predict the reasons when a customer leaves their company.

E-commerce, Amazon

____ websites use Data Mining to offer cross- sells and up-sells through their websites. One of the most famous names is ____, who use Data mining techniques to get more customers into their store

Supermarkets

Data Mining allows ____develope rules to predict if their shoppers were likely to be expecting. By evaluating their buying pattern, they could find woman customers who are most likely pregnant. They can start targeting products like baby powder, baby shop, diapers and so on.

Crime Investigation

Data Mining helps _____ agencies to deploy police workforce (where is a crime most likely to happen and when?), who to search at a border crossing etc.

Bioinformatics

Data Mining helps to mine biological data from massive datasets gathered in biology and medicine.

• Market Analysis

• Fraud Detection

• Customer Retention

• Production Control

• Science Exploration

The information or knowledge extracted so can be used for any of the following applications:

Customer Profiling

Data mining helps determine what kind of people buy what kind of products

Identifying Customer Requirements

Data mining helps in identifying the best products for different customers. It uses prediction to find the factors that may attract new customers.

Cross Market Analysis

Data mining performs Association/correlations between product sales.

Target Marketing

Data mining helps to find clusters of model customers who share the same characteristics such as interests, spending habits, income, etc.

Determining Customer purchasing pattern

Data mining helps in determining customer purchasing pattern.

Providing Summary Information

Data mining provides us various multidimensional summary reports

Finance Planning and Asset Evaluation

It involves cash flow analysis and prediction, contingent claim analysis to evaluate assets

Resource Planning

It involves summarizing and comparing the resources and spending

Competition

It involves monitoring competitors and market directions

frauds

Data mining is also used in the fields of credit card services and telecommunication to detect ____

• Business Understanding

• Data Understanding

• Data Preparation

• Data Transformation

• Modeling

• Evaluation

• Deployment

Data Mining Implementation Process:

Business Understanding

In this phase, business and data-mining goals are established

Data Understanding

In this phase, sanity check on data is performed to check whether its appropriate for the data mining goals.

Data Preparation

In this phase, data is made production ready

data preparation

The ______ process consumes about 90% of the time of the project.

Data cleaning

_____ is a process to "clean" the data by smoothing noisy data and filling in missing values

Data transformation

______ operations change the data to make it useful in data mining

Data transformation

_____ operations would contribute toward the success of the mining process

Smoothing

It helps to remove noise from the data

Aggregation

Summary or aggregation operations are applied to the data

Aggregation

the collection of related items of content so that they can be displayed or linked to.

Generalization

In this step, Low-level data is replaced by higher-level concepts with the help of concept hierarchies.

Normalization

_____ performed when the attribute data are scaled up or scaled down

Attribute construction

these attributes are constructed and included the given set of attributes helpful for data mining

Data transformation

The result of this process is a final data set that can be used in modeling

Modeling

In this phase, mathematical models are used to determine data patterns

Forecasting

Estimating sales, predicting server loads or server downtime

Risk and probability

Choosing the best customers for targeted mailings, determining the probable break-even point for risk scenarios, assigning probabilities to diagnoses or other outcomes

Recommendations

Determining which products are likely to be sold together, generating recommendations

Finding sequences

Analyzing customer selections in a shopping cart, predicting next likely events

Grouping

Separating customers or events into cluster of related items, analyzing and predicting affinities

Evaluation

In this phase, patterns identified are evaluated against the business objectives

deployment phase

In the _____, you ship your data mining discoveries to everyday business operations

• Classification

• Clustering

• Regression

• Outer

• Sequential Patterns

• Prediction

• Association Rules

Data Mining Techniques:

Classification

This analysis is used to retrieve important and relevant information about data, and metadata. This data mining method helps to classify data in different classes

Clustering analysis

____ is a data mining technique to identify data that are like each other. This process helps to understand the differences and similarities between the data

Regression analysis

_____ is the data mining method of identifying and analyzing the relationship between variables.

Association Rules

This data mining technique helps to find the association between two or more Items. It discovers a hidden pattern in the data set

Outer detection

This type of data mining technique refers to observation of data items in the dataset which do not match an expected pattern or expected behavior.

Outer detection

This technique can be used in a variety of domains, such as intrusion, detection, fraud or fault detection, etc.

Outlier Analysis, Outlier mining

Outer detection is also called ______ or ______.

Sequential Patterns

This data mining technique helps to discover or identify similar patterns or trends in transaction data for certain period

Prediction

_____ has used a combination of the other data mining techniques like trends, sequential patterns, clustering, classification, etc.

Prediction

It analyzes past events or instances in a right sequence for predicting a future event.