In simple terms, ETL is the process of transferring data between two particular locations using three important steps. The first step is the extraction step in which data is read from various sources and databases. The second step is the transformation step in which the extracted data is converted into a particular format so that it gets ready for the loading stage. In the next stage, we copy the data to a targeted location which is an entirely different system. In this article, we trace the evolution of ETL from traditional to modern times.
Back to traditional ETL
In the past, we stored our data in operational databases before we marched into the ETL era. This allowed us to transfer data between the source and the sink promptly. That said, there were some complications and disadvantages associated with this process. Traditional ETL conversion architecture processed various types of files in a batch-wise manner. This was relatively a time-consuming process and prevented the processing of a single file that was mined out from a particular data warehouse. Moreover, the disadvantage associated with traditional ETL tools was that the processing of sensor data, matrix data, and other types of data could not be done in real-time. In addition to this, a global schema was required to execute data modeling for a very large domain. In the present times, we tend to process data in real-time. As such, we conclude that a time-consuming and resource-intensive process has very few applications in the present time. That said, the order of big data continues to grow and the traditional ETL structure tends to become outdated and redundant.
The present state
In the age of Big Data Analytics, the usage of data has undergone a paradigm shift. We have seen a huge drift in the processing capabilities of traditional and modern technologies. The capability to process real-time streaming data is the cornerstone of modern ETL processes. The replacement of single server databases by platforms like Cassandra and elastic search is a really big achievement in itself. The advancement of data processing capabilities and data capture technologies has shown that modern ETL infrastructure is the need of the hour. Advancements in data cleansing have been such that they have exactly met the requirements of modern business entities.
The functions of modern ETL systems
The problem with the traditional ETL system was that it is used to dump different types of data into warehouses that were available for processing in batch wise manner. This problem has been overcome in the modern ETL systems. The modern ETL system processes files in a real-time manner. It processes different types of events including the event-centric data via the server. The ability to store data in multiple locations and access it at the time of our choosing is an added advantage. The process of monitoring is given serious consideration and periodic notifications are sent in case of anomalies.
A review of streaming architecture
In the initial stage, we need to make sure that all application programming interface connects simultaneously to a large number of data sources. Traditionally, only the source and the sink used to be connected. Different types of data schemas are used in our architecture. So, it becomes necessary to rely on data mapping that processes different types of data from various sources to a common platform. It is on this platform that further processing can be done. Standalone components in the traditional infrastructure like files and CDC are connected by streaming architecture. The advantage of modern streaming architecture is that it allows us to analyze the events generated from legacy systems in a time-bound manner. In this way, different types of computations can be performed with a lot of ease on the data sets of our choice. In addition to this, we can use different types of visualization tools to summarise our data sets for effective presentation and comprehension. Last but not least, we can also change the business logic as per our requirements without making any changes to other components.
Concluding remarks: Resolving the dilemma for choosing an ETL service providerThere is no dearth of ETL technology providers in the present times as we witness a stiff competition to provide cloud based services at reasonable costs. One of the leading service providers in this domain is Impetus technologies which provides great technical expertise related to ETL.
