Data Consolidation is a process of summarizing large quantities of information in a spreadsheets which is a part of one large worksheet that going to reflect all the collected data. Data consolidation is performed by computers, common example of this is Microsoft Excel that contain automated tool for data consolidation. It is a process that take data from various cells across the spreadsheet and compile into another sheet. We can say this is a consolidation system that save the user time and data and manually enter that data on the desired place by doing this make it easier to re-arrange, format and organize with the large quantity information within less time. All the process we discussed above are the part of three data integration techniques. So the data consolidation techniques include ETL and ELT.
ELT stands for Extract, Load and Transform defines a variation process of data consolidation in which bulk amount of data has been transformed and loaded on to the desired place. Once the data has been loaded then it transform into tables and where the same data can be accessed by the end users. Sometimes it is also known as pull-system because the transformation is initiated only on demand. This system will allow user to work on transformed and published data where information is pulled after loading the data into tables.
ETL stands for Extract, Transform, Load is one another data consolidation technique which is differ from ELT in some steps. This technique extract the data from many different sources and then transform the data according to prescribed protocols and load the resultant data to some target place in specified file format. ETL is different from ELT in some places like it transform the data before loading cycle. The reason many organization prefer ELT is reduction in load time which is relative to the ETL model. So the model take advantage of the processing capability built in warehousing which reduce the time and more cost effective.
Now we are going to discuss terms we used in Data consolidation techniques in more explanatory way. Get help in Data consolidation and also know about what is consolidation from our expert tutors in database assignment. Students can also submit their requirement by click here.
Extraction is first involving stage in both the techniques of data consolidation which extract data of high volumes that place on heterogeneous sources. Data may be carried out in many database models like relational, hierarchical and object databases with some structured and unstructured out of files that may also include outside source whether they depending on industry and data relevance.
In both the data consolidation system this stage is varied and depends on simple procedure and complex procedure. Simple procedure like file type conversion and complex procedure like logic-based manipulation and integration. This stage will allow data to customize and suitable information for use internally. Organization streamline the transformation process by carry out data operation on collected data but that depends on industry, its scope and volume of business.
This stage is also varied in data consolidation techniques which refers to transfer data to a target application. In ELT, the data loaded is unprocessed, but ETL is opposite of ELT. The loading. This stage modify the system based on data acceptance metrics which allow both bulk and trickle modes for each data element in the loading cycle.