Data Processing:(Data Pre-Processing)-
Data processing is best example for getting well form data from unstructured or noisy data. If data processing complete then we can getting a perfect information for knowledge base. In data warehouse lots of information are saved but not getting knowledgeable part in that information. In that data is incomplete noisy and inconsistent also they have duplicate data. Data processing filters can work on data and read data, cleaning data,integration,data transformation and data reduction task.
we discuss each task as follows-
1. Data Selection-
In data selection the all data coming from Real world data,that all data collected and that data are selected with well manner also they all data are integrated for next stage. In data cleaning Mainly task for cleaning, also work on input or missing values, reduce the noisy data and maintain the consistency of data.
2. Data Transformation-
The data transformation is important stage in data processing. It applies a set of rules to transfer the data from source to target and that also working on converting data into same dimensions. They also working for aggregates generating ,sorting ,deriving new calculated data, and validation rules.
3. Data Integration-
Data integration combining all data for next stage and pass the data to data Reduction.
4. Data Reduction-
The data reduction works on variables and data for reducing their size and compromising the integrity of original data up to producing a quality knowledge. In that stage data cube aggregations,dimension,reduction data compression works done successively. That all strategies are used for data reduction. The reduction method data can be calculated or reduced well in manner and gives a proper knowledge to end user.