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Extract, Transform and Load is also called as ETL. ETL plays a major factor in strategies related to data integration. The ETL permits the businesses to assemble and collect data from various sources and merge it into an exclusive centralised place.

It enhances and assists the process of multiple data to work collectively. Extract Transform and Load ETL assignment help online from BookMyEssay is availed by students as everything related to ETL is explained in detail by the faculty. Moreover, the content provided by them is self-explanatory and easy to understand.

In Extraction, data are read and collected from multiple databases. In Transformation, the extracted data are converted from its original form into a new form so that it can be put into another database. At last, in loading, the data are assigned to the selected database.


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History of ETL

ETL came into the picture and became popular is the mid1970s. This was the period when body corporates started using multiple data in order to store various information related to business. Data integration turned out to be a key factor and hence, ETL became the conventional method of collecting data from different sources and then transforming them prior to loading the data to the final database.

In the 1990s, the concept of data warehouses came into the scene. The data warehouse helped in providing an integrated entry to data collected from multiple systems such as minicomputers, spreadsheets, mainframe computers and personal computers. Over time, various formats of data, systems and sources grew and expanded.

Importance of ETL

The business houses depend on the process of ETL in order to obtain an amalgamated view of the data. These data help in taking various businesses related decisions. ETL is of huge importance. The Extract Transform and Load ETL homework writing services have explained and highlighted the importance of Extract, Transform and Load in a very effective manner. One of the points is that ETL supplies in-depth historical information to the businesses, generally when used along with a warehouse (enterprise data). As the ETL provides an amalgamated perspective, it becomes facile for the businesses to read, analyse and then report the relevant data.

Codifying and reusing a data that moves without technical expertise to write scripts and code enhances data productivity and this is where ETL helps. It is important to improve and evolve with time in order to sustain in the market. ETL has also done the same. It has evolved and improved with time so that it supports the upcoming requirements related to integration such as streaming data. Many times the business houses use both ELT and ETL so as to bring the information together, continue accuracy and furnish data which are required by the warehouses.


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How ETL Works

We might have got an idea regarding the steps those as involved in the ETL process. It is important to have a detailed knowledge of the same. The steps have been explained in the help for assignment with Extract Transform and Load ETL as follows:

  • The first step is of Extraction. In this process, the unstructured as well as structured data is gathered and merged into one repository. The primary data can be obtained from various sources which include cloud, marketing and sales applications, CRM systems, Data warehouses, existing legacy systems and databases, mobile devices and other applications and analytical tools. ETL tools help in automating the process of extraction which leads to efficient and dependable workflow.
  • The second step is transformation. In this stage of ETL, various rules are applied so as to make sure that the quality of data is best and it is easily accessible. There are sub-processes involved in this phase such as cleaning, standardization, deduplication, verification, sorting and other tasks. This step is regarded as the most vital part of ETL process.
  • The last step is loading. In this stage, the newly transformed data are loaded in a new destination. The loading can be done in two ways. One way is fully loading and other is incremental loading.

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