introduction to business intelligence and data mining
DESCRIPTION
TRANSCRIPT
Rajesh Math
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BI I Lecture 1
Syllabus/Course
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Same group for communicationSyllabusBooksTools/SoftwareTitle of Course is BI
Data Mining
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Data Mining is process of exploration and analysis by automatic or semiautomatic means of large quantities of data in order to discover meaningful patterns and rules.
Data Miners are the people who apply this potent mixture of massive computing power, clever algorithms, business knowledge and human intuition.
What Data Mining Can Do ?
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Activities that are to extract meaningful new information from the data.
The activities are :1. Classification2. Estimation3. Predication4. Affinity grouping or association rules.5. Clustering 6. Description and visualization
Classification
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e.g. i. Classifying credit applicants as low,
medium or high risk.ii. Assigning customers to predefined
customer segments.iii. Assigning key-words to articles as they
come off the news-wire.
Estimation/Prediction
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Use modeling to estimate the probability
e.g. estimating the value of a real estate.(MLS in US)
Prediction: It can be thought as combination of classification and estimation but the difference is in emphasis i.e. we wait to see if our prediction is correct.
E.g. Predicting if customer will move away
Affinity Grouping or Association Rules
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To determine what things go together.e.g. Retail Chains can arrange items together
that are purchased together.Used to cross sell different opportunities.
Clustering
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Task of segmenting a diverse group into a number of more similar subgroups or clusters
Different from Classification is absence of predefined classes rather records are grouped together on the basis of self-similarity
Normally a first step before doing something else e.g. Before ‘What type of promotion works best for customer ?’ divide people into clusters of similar buying habits.
Data Mining Discovering Knowledge based on Data
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Descriptive ModelsDiscovery of patterns & relationships in the underlying datae.g. A customer who purchases diapers is 3 times more
likely to buy beer.e.g. There is a cluster of households w $60-80K incomes and
2 cars (more than ($60-$80k and 1 or 3 cars, or 2 cars w $40-60K or $80-100k) who have recently bought life insurance.
Predictive Models & Anomaly DetectionPredictions of trends & behaviors;
Noticing deviations from those predictionse.g. How much profit will this customer generate? Is this
credit card stolen? Uses
Sales & Marketing, Diagnosis, Fraud Detection, …
Data mining
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Simply describe what is going on complicated database to better understanding of people products or process that produced the data.
Data visualization : one powerful form of descriptive data mining. i.e. one picture is worth many thousand association
In business context knowledge out of data-mining can be used to lower costs or raise revenue.
Data mining as Research Tool
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Pharmaceutical Industry to develop leads on binding molecules.
Bioinformatics is based on data mining which interprets data being generated by high throughput screening and mapping of the entire human genetic sequence.
Data Mining for Marketing
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Used to do target marketing for right customers.
Prospective targets of a marketing campaign.
Identify trends/events that correlate
Data Mining For CRM
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To make the customer data into meaningful information
Good CRM means providing a good image of company across multiple channels.
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BI Definition
Business intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.
BI Applications
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Business intelligence applications can be: Mission-critical and integral to an
enterprise's operations or occasional to meet a special requirement
Enterprise-wide or local to one division, department, or project
Centrally initiated or driven by user demand
BI Goal
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Main business intelligence goal is to provide sufficient information for making business decisions. Depending on the aim of the business decision, business intelligence methods can provide information about company customers, market trends, effectiveness of marketing campaigns, companies competitors, or even predict future activities.