What is data mining?
Data mining which is also known as knowledge discovery is the process in which we extract useful information from the large set of the data.
What is the need for data mining?
Now a day daily an enormous amount of data in generated, a survey says that 90% of all the end the word is produced in past few years. If we talk about the big data, most of the data generated daily is in the form of unstructured data.
We are living in the data age where in every place you can see the data generation, if you are standing in queue for making reservation on the train at this location a significant amount of data is generated continuously.
Business society, medical field, science and engineering and every aspect of life is producing a large amount of data daily.
Our telecommunication companies are making tens of petabytes data every day. Medical science and health industry are also generating a significant amount of data daily. Search engines where billions of web searches os done daily is producing tens of petabyte data daily.
Our social media become the significant source of data generation. Daily a large number of post, status, videos, pictures are uploaded on social networking sites.
Scientist, engineering field, research centers are also generating a significant amount of data daily.
We know that all data is not relevant for us but there is some data which is important for us but retrieving the valuable information from the vast data set is not an easy task.
Data mining is a tool which is used to knowledge mining from the large set of data. With the help of data mining we can retrieve the valuable information from the huge amount of data and make the data usable for analytical purpose, for business use, etc.
Data Mining in Medical Science
Medical science field is generating an enormous amount of data per day, so mining of that is necessary for getting useful information from that.
Data mining helps in medical science to
- Detect fraud abuses in medical/hospitals
- For making customer relationship, it helps for exploring the business.
- Doing patient activity analysis, how many visits they did and for which reason.
- To identify successful therapy for different illnesses.
Data Mining in Marketing/Sales
- In marketing data mining is very efficient and useful tool, all marketing analyst use data mining to analyses the customer behavior what they are buying, and according to that they make the offers for them.
- They mine the data according to customer purchase, that what they missed, what they are looking again and again, what is the range of spending money of the customer according to that they plan their business.
Association Technique for Data mining
Association is a data mining technique, in this technique we discover the pattern and make the relationship between items in a large data set.
With the help of association rule market analyst analyze the customer behavior according to see their buying pattern.
I would like to give a real time example if you are visiting a online shopping website to see the mobile phones then they start to give you suggestion you may also like this, this item also looks like your perceived thing, etc.
It means they are analyzing your buying or something looking pattern. And this done through the association rule.
Classification Technique for Data Mining
It is a classic technique for data mining. This method depends on predictions, here we classify the data in some groups or individual. Predictions are done by some predefine techniques.
First of all we will see an example of classification, a bank officer who has the authority to approve the loan of any person then he has to analyses customer behavior to decide passing the loan is risky or safe that is called classification.
Clustering Technique for Data Mining
Clustering is a technique used in data mining, in this technique we group the objects which have similarity sometimes it may differ.
This technique is used in machine learning, pattern recognition, information retrieval, image analysis.
Our project Autism Database Center:
Autism Spectrum Disorder (ASD) is a complex neurological disability that typically appears during the first three years of life and impacts development of social interaction and communication skills. Each individual is affected differently and in varying degrees, from milder forms in which intellectual ability is high but social interaction is low, to severe cases typified by cognitive impairment and maladaptive behaviors. ASD is estimated to affect 1 out of 68 children at the age of 8, with males being four times more likely to develop it than females. In addition, about 30% of children with ASD develop epilepsy at later stages. There is no cure for autism. Treatments are available which can improve outcomes; however, these are most effective when begun at an early age. Early intervention is the best indication for positive outcomes; when started early, the costs of treatment can be reduced by almost 70% annually. The main goal of this project is to develop a comprehensive system that can resolve autism end phenotypes and help clinicians deliver personalized treatments to individuals with autism spectrum disorder (ASD) through the use of “Big Data”—the amalgamation and processing of large, heterogeneous datasets—comprising structural imaging, functional imaging, genomic data, and behavioral data.
- Social media mining is the process of representing, analyzing, and extracting actionable patterns and trends from raw social media data. … It encompasses the tools to formally represent, measure, model, and mine meaningful patterns from large-scale social media data.
- Customer inputs and data analysis every customer has his own data that is part of information that our system can analyze.
- Web content data mining refers to any project with a primary focus of extracting data from a website, focusing on specific data points about Autistic.
Expected output of this project:
- Analysis for data in deferent reports.
- Behaviors of Autistic kids and their Families.
- Products and equipment used.