Construction Of A Data Warehouse

Data in computerized form is discoverable, even if the paper “hard copies” of the information have been produced. The producing party can be required to design a computer program to extract the data from its computerized business records.

Extraction, Transformation, and Loading processes are responsible for the operations taking place in the back stage of a data warehouse architecture. In a broader aspect, initially the data is extracted from the source data stores which could be On-Line Transaction Processing or Legacy system, files of any formats, web pages or any other documents like spreadsheets or text documents. In this step, only the data which is different from the previous execution of ETL process (newly inserted, updated) gets extracted from the sources. Next, the extracted data is sent to Data Staging Area where the data is transformed and cleaned. Finally, the data is loaded to the central data warehouse and all its counterparts e.g., data marts and views. (Kabiri & Chiadmi 2013, p.1)

24) Before it can be loaded into the data warehouse, operational data must be extracted and

Extraction: This is the process of extracting any evidence that is found relevant to the situation at hand from the working copy media and subsequently saved to another form of media as well as printed

In order to extract the information I require and want I utilize the following methods;

Specialized techniques for data recovery, evidence authentication and analysis of electronic data far exceeding normal data collection and preservation

The databases are required to be accessed very properly; the broken or fragmented data needs to be recovered. For querying and reporting purposes the data should be easily accessible

Most of the time we might have to clean and process the data to find some hidden insights in the data. This is called data processing.

Information collected digitally from computers or media storage applications has protocols that need be followed during the process. The order of collecting digital information mostly determines the life expectancy of information collected (Eoghan, 2004, p. 74). There is a need to change information

imaging application. This is because the crucial data required for the classification phase are derived at this stage. Feature extraction is the process of estimating

31) The authors refer to the data model produced by reverse engineering as the RE data model.

The data information also included the component of the data collection, the operational definition, the type of analysis, and the location in the program file.

Chapter 2 describes the Avalon data warehouse functionality and chapter 3 the scope of the Avalon data warehouse. Chapter 4 lists the motivation for supporting the Avalon data warehouse implementation. In chapter 5, the process of collecting and processing business requirements is described. At chapters 6 and 7, there is a technical description of the architecture and data security, and Chapter 8 outlines the implementation plan.

As the reader has got now all the information available about theory and methodology, it’s time to move on to the concrete part. Indeed, next header explains the extraction of data.

The data file consists of lots of entities, which needs to extract the data according to the given format. And to do the analysis, an algorithm is developed according to the hierarchy as given in the excel worksheet, and a graphical user interface (GUI) to visualize the output of data.