ETL is Extract, Transform and Load. It is basically a process that ‘extracts’ the data from numerous sources, then ‘transforms’ them by applying calculations, concatenations etc. and lastly ‘loads’ the data into Data Warehouse system.

It may seem to you like a simple process wherein data warehouse creating is just all about extraction, transforming and loading. However, the process, in reality, is quite complex. The process involves constant monitoring and inputs from experts like developers, testers, analysts, and top executives.  Also, this process is a recurring activity on a daily, weekly or monthly bases and need to be very well documented, automated and agile.

So, what are the many benefits of adopting ETL?

Why do you need ETL?

 

We can give you more than one reasons as to why your organisation needs ETL.

  1. With ETL, companies can better analyse their business data and take more informed business decisions.
  2. ETL makes data migration into a data warehouse possible and easier. You can convert data into different formats and types to maintain uniformity and consistency.
  3. Your transactional databases will not be able to give you all answers regarding complex business needs that ETL can easily do.
  4. With ETL, you can compare sample data between the target and the source system.
  5. It also helps to enhance productivity since it can code and reuse data without the need of any specific technical skills.
  6. ETL also facilitates rules regarding data transformation, aggregation and calculation.
  7. The Data Warehouse automatically updates when the data source changes.

 

The ETL Process: Various Steps

 

We will now look at the various steps in the ETL Process in brief.

Step 1 – Extraction

This is the first step of the ETL architecture. This step mainly involves the extraction of data from the source to the staging area.All necessary transformations are also carried out here in the staging area so that the source system doesn’t get disturbed. The main sources may include some of the legacy applications like customised applications. ERP, text files, Mainframes etc. Therefore, Data warehouse should be able to integrate systems with varying DBMS, OS and communication protocols.

So, before proceeding with data extraction, you must have a logical data map that will clearly define the relationship between the target and the source data.

Basically, there are three Data Extraction methods:

  1. Full Extraction
  2. Partial Extraction without update notification.
  3. Partial Extraction with update notification

 

Step 2 – Transformation

The data that we have extracted in the first step is usually in its raw form and cannot be used. Therefore, it has to undergo cleaning, mapping and proper transformation. This is the main step where ETL actually adds value to the extracted data to generate insightful business reports for you. There can be some direct move or pass through data – the data that doesn’t need any kind of processing and transformation.

One important highlight of this step is that one can carry out customised data operations. Say, for example, if the first name and the last name in a table is placed in two different columns, with the help of ETL, you can concatenate them before proceeding to loading.

Some of the data integrity problems include use of different names like Cleaveland and Cleveland, multiple denotation of company names, different spellings of the name of the same person and blank fields in some files.

Some of the validations to be done at this stage include character set conversion and encoding handling, using lookups to merge data, conversion of units of measurements for uniformity, transposing rows and columns and so on.

Step 3 – Loading

This is the last step in the ETL Process. Considering a typical data warehouse, usually there are large volumes of data that need to be loaded in short periods of time. This calls for an optimisation in the performance of the loading process.

We also have to have a backup plan in mind in case of load failure. There should be good recovery mechanisms that will restart the process from the point where it failed and ensure no loss of data and integrity. The admins have to monitor, resume and cancel loads according to the performance of the server at that point in time. There are three types of loading:

  1. Initial Load — where you populate all the tables in the data warehouse.
  2. Incremental Load — where you can apply ongoing changes on a need basis.
  3. Full Refresh —where you can erase the contents of one or more tables and reload completely new data.

 

Some of the popular ETL Tools

 

While there are many available Data Warehousing tools, let us look at some of the most popular and widely used ones.

  1. Oracle

This has been the industry-leading database for quite some time now. With its wide range of choices in data warehouse solutions, it helps to optimise user experiences and enhances operational efficiency.

Check it out here: https://www.oracle.com/index.html

2. MarkLogic

This solution makes data integration very easy and fast, thanks to its range of enterprise features. It is capable of querying multitudes of data like metadata, relationships, documents etc.

Check it out here: https://www.marklogic.com/product/getting-started/

3. Pentaho

Pentaho is a business intelligence software. It provides the following services: data integration, data mining and extract, transform and load capabilities, OLAP services, information dashboards, reporting etc.

Check it out here: https://www.hitachivantara.com/en-us/products/data-management-analytics.html

So, we now have a basic idea of the ETL Process and how it is carried out. There are a few things that you need to keep in mind to ensure that your process is as smooth as possible. You must never try to clean all the data as it would take a lot of time and effort and may cost you a fortune! To speed up query processing, you should have auxiliary views and indexes. Similarly there are some other aspects that you must be aware about the ETL Process.

But, if you are not and you don’t want to worry about all these technicalities, you can simply reach out to us for all your data warehouse needs! Experts at EOV have years of experience in the best practices in ETL and will surely help you carry out the process of extraction, transformation and loading in the most hassle-free manner! Get in touch with us today!