Building a hadoop ETL system is a challenging job as it is heavily constrained by unavoidable realities. The development team working on ETL system must live with data format of current system, clear business requirements and a clear idea of available legacy system. In this article, professionals will make you learn how to analyze the bulk ETL data with efficiency. You can follow the instructions shared below and make an analysis report yourself.
In the recent years, the term Data is the new oil has become more famous because of the Hadoop ecosystem. In past few years, organizations have made a transition to use big data as a tool for business analysis and future trends. In order to analyze the huge amount of data which is being generated from various different sources, more and more sophisticated warehouses are required.
The Extract-Transform-Load (ETL) System is the Foundation of the Dataware House
From a high level point of view, the ETL process is a process of converting the data from various sources, cleaning the data and loading the data into a warehouse.
A properly designed ETL system extracts the data from various sources, maintains the consistancy standards, enforces the quality of data, confirms the data so that seperate sources can work together and finally delivers the data in a common presentation ready format so that the other application developers can use the data and the strategic managers can do better business analysis and reporting.
In this article I am going to describe a simple approach of analysing and designing an ETL process. Building an ETL system is a challanging task because it is heavily constrained by unavoidable realities.
The ETL development team must live with clear business requirements, the data format of the current sytem, its dependencies and they must have a clear idea regading existing legacy system.
The two concurrent threads must kept in mind while designing and building an ETL system.
- Planning and Designing Thread
- Dataflow Thread
From very high level view both the above threads are simple.
The above image of planning and designing stage is a very high level view of the phase.
Indeed each stage of above diagram can be sub divided into multiple sub stages.
The above two threads of developing ETL are simple scenario of designing an ETL. The ETL process may be more sophisticated based on the organization’s requirement.
You have just read the instructions that will assist you in analyzing the hadoop ETL data like professionals. You can now follow the above steps and analyze the huge amount of data in a limited time frame.
