Data analysis is the process of finding useful information in the given data set, summarizing it in form of reports which leads in better decision making to achieve the business goals. In case of data analysis size of data set is small as compare to data mining, so we can not see data analysis and data mining (based on artificial intelligence) as same thing. There are many other differences between data analysis and data mining.
Data analysis can be quite simple or to complicated depending upon the nature of the problem. For example when you go to buy some product you may ask few questions regarding features, cost and price of the product. You may also ask for substitute for that particular product, and in the end you analyze the things (cost, price and features) and made your decision about which product to buy. So in this case data analysis is quite simple because there is no data set involved, you got exact information without digging through data. But in real business problems it can be complicated where you have to extract the data from database into such tools where you can analyze the things. For example you can extract external (
SQL Server, Oracle Server, MS-Access, CSV files etc) data into excel. You may have to extract data form more then one external sources and merge the data together to analyze it. Once data is available it needs to be proper formatted. Then you have to dig through the data to find required information. Once it is done, you need to create reports because Top Management is always interested in reports to make decision making. They are not concerned about how you did all the things they need only final results from you. So it all depends upon the nature of the problem.
What sort of analysis you need to perform depends upon the data you have and nature of the problem. Data anlaysis can be divided into two categories:
Qualitative Data Analysis
Qualitative Data comes from:
1.Observations
2.Interviews
3.Questionaries
4.Documents(text data)
Quantitative Data Analysis
Qualitative/Quantitative Data can be categorized as:
Nominal
Ordinal
Interval/Ratio (Discrete/Continuous)
