What is Data mining? It’s the repossessing of hidden information from data using algorithms. Data mining helps to extract useful information from great masses of data, which can be used for making practical interpretations for business decision-making. It is basically a technical and mathematical process that involves the use of specifically designed software (example Sisense and Neural Designer).
Data mining is gaining a lot of importance because of its vast applicability. It’s being used increasingly in business applications for understanding and then being able to predicting valuable information, like customer buying behavior and buying trends, profiles of customers, industry analysis, etc.
Some of the main applications of data mining are in direct marketing, e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities.
Data Mining tools
Some of the most popular data mining tools are: decision trees, information gain, probability, probability density functions, Gaussians, maximum likelihood estimation, neural networks, instance-based learning /case-based/ memory-based/non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, K-Means and hierarchical clustering.
Techniques and Process of Data Mining
- Data Collection
Data collection is the first step required towards a constructive data-mining program. Almost all businesses require collecting data. It is the process of finding important data essential for your business, filtering and preparing it for a data mining outsourcing process. For those who are already have experience to track customer data in a database management system, have probably achieved their destination.
- Algorithm selection
You may select one or more data mining algorithms to resolve your problem. You already have database. You may experiment using several techniques. Your selection of algorithm depends upon the problem that you are want to resolve, the data collected, as well as the tools you possess.
- Regression Technique
The most well-know and the oldest statistical technique utilized for data mining is regression. Using a numerical dataset, it then further develops a mathematical formula applicable to the data. Here taking your new data use it into existing mathematical formula developed by you and you will get a prediction of future behavior. Now knowing the use is not enough. You will have to learn about its limitations associated with it. This technique works best with continuous quantitative data as age, speed or weight. While working on categorical data as gender, name or color, where order is not significant it better to use another suitable technique.
- Classification Technique
There is another technique, called classification analysis technique which is suitable for both, categorical data as well as a mix of categorical and numeric data. Compared to regression technique, classification technique can process a broader range of data, and therefore is popular. Here one can easily interpret output. Here you will get a decision tree requiring a series of binary decisions.
Data Mining Play significant role in Corporate Industry
A large amount of information is collected normally in business, government departments and research & development organizations. They are typically stored in large information warehouses or stores. For data mining tasks suitable data has to be extracted, linked, cleaned and integrated with external sources. Data mining is the automated analysis of large information sets to find patterns and trends that might otherwise go undiscovered. It is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, telecommunications and so on. Data Mining is based on mathematical algorithm and analytical skills to drive the desired results from large database collections.
Why Outsourcing Data Mining Services?
Are huge volumes of raw data waiting to be converted into information that you can use? Your organization’s hunt for valuable customer information ends with data mining your past processes and transactions, which can help to bring more accuracy and clarity in future decision making processes.
Nowadays the world is information hungry and with Internet offering an easy means of communication, there is remarkable flow of data. Making sure your data is available and in a readily workable format would be of great help to your business’s overall decisions and goals. This filtered data is of considerable use to an organization (allowing for modification of services more honed to their customer needs) as it increases profits, improves smoother work flow and ameliorating overall risks.
Data Mining services include:
- Congregation data from websites into excel database
- Searching & collecting contact information from websites
- Using software to extract data from websites
- Extracting and summarizing stories from news sources
- Gathering information about competitors business
Advantages of Outsourcing Data Mining Services:
- Skilled and qualified technical staff who are proficient in English
- Improved technology scalability
- Advanced infrastructure resources
- Quick turnaround time
- Cost-effective prices
- Secure Network systems to ensure data safety
- Increased market coverage
In a Nutshell
Data mining brings the company closer to its customers. The real winners here, are the companies that have now discovered that they can make a living by improving the existing data mining techniques. They have filled a niche that was only created recently, which no one could have foreseen and have done quite a, good job at it.