There has been a common debate surrounding automated ETL programming and hand-coded programming in an organisation. ETL stands for Extract Transform Load which is a procedure in the process of data preparation. The job is to integrate and make the data available for the further analysis.
According to consultant Rick Sherman, “In many companies, data integration remains a manual task — by choice. But it might be time to automate that process.” But it is really worth getting ETL tools for your business? Let’s take a look.
ETL Vs Manual Programming
Here are some ways in which both the methods can be compared:
1.Time: Hand-coded methods can take days or even weeks, depending on the amount and complexity of the data, to only prepare the data for the analysis, even before any analysis is done. For example, if the sales data has to be compiled into a single sheet considering various parameters and then given further for analysis, hand-coding would take many days to prepare the data. If instead ETL tools are used, it will do the job accurately and within a time frame much less than that need by the hand-coded method. ETL comes in rescue big time as a time-saver.
2.Reusability: Processes in ETL method can be saved and directly reused for other processes and data models as well. In manual coding, changes will have to be made meticulously, by a programmer. Instead, his time can be saved and be spent on genuine problems.
3.Management: Because of automation, managing datasets has become easy with ETL programming. ETL tools provide one a larger view of ETL processes, with things like where the data is coming from, where it is going and what sort of calculations have been done on it. By doing this, ETL method helps in a way that a manually crafted code will never be able to replicate. Such advantages makes ETL processes preferable as it makes data management more easy. Applying hand-coded programming on these complex structured and unstructured data, saves several lines of code. Meanwhile, automated coding does it with minimal efforts. A visual ETL layer also helps in making the process very transparent. Also, every change is easily noticeable and easy to retract and hence saves the times that one spends in hand coded programming and finding the error in the code to locate changes that are initiated by one programmer of the team who is currently unavailable.
Moreover, all data, no matter how large it is, can be taken and used for analysis, as opposed to hand-coded programming, which requires the programmer or developer to take a sample data to test their program. This also adds to saving time.
Why Not All Companies Have Adopted ETL?
ETL, specially for large datasets, works the best. But many organisations with large datasets have not popularly adopted the ETL methods. Every ETL tool has its own unique logic and some applications might find restrictive. But hand coded programming comes with endless possibilities and it is quite flexible that way. In manual programming, data can be managed directly and organisations find that convenient. . We have a complete control over the program, but in ETL there are parameter settings of the ETL tools that you cannot just have a control.
Also, manual coding is quick and easy to move data and is hence cheaper than ETL. It’s easier to get the data into a report. Many organisations find ETL tools expensive and so they avoid using it.
In case of large datasets, where extensive data preparation is required, ETL comes with a huge advantage. It provides a cleaner, better experience than manual coding. ETL comes in very handy when the processes are very easy to automate and the task is not that complicated, but not otherwise. It makes sense to always use ETL, since it has many more advantages over manual. Unless there is a strict cost constraint or a problem where strictly a manual intervention in a problem is necessary, manual coding should be preferred. Otherwise, ETL is a always a preferred choice.
Subscribe to our NewsletterGet the latest updates and relevant offers by sharing your email.
Found a way to Data Science and AI though her fascination for Technology. Likes to read, watch football and has an enourmous amount affection for Astrophysics.