We know that ETL is the process of extracting data from multiple source systems, transforming them to adapt them to the needs of the business and loading them into a destination database. The vast majority of companies have large amounts of data, often accumulated for years. However, it is very likely that this data is stored in different places and in different formats, which makes it difficult to exploit and extract knowledge. That’s why ETL and data pipelines solutions are in demand in any business field.Â
If you want to get maximum benefit from the opportunities offered by the data, you need to first organise them and consolidate them in a single place, typically a data warehouse (Data Warehouse). It means that your companion in this process is an ETL tool.
Special characteristics of the ETL process
Each company has different data and different needs. However, there are features common to every ETL process such as:
- Complexity;
- Continuity;
- Criticality.
Companies can find large amounts of data stored for many years and generated by their different departments, for example:
- financial,
- engineering,
- marketing,
- sales, etc.
In addition, this data is distributed and isolated – in different silos: relational database, CRM, marketing automation tools, customer service solutions, among others. Extracting and consolidating all this information is an extremely complex task.
In order to perform accurate analyses, it is necessary to keep the Data Warehouse constantly updated. For this reason, it is important that the ETL process is performed at regular intervals, detecting changes in the information contained in the sources, extracting the new data, transforming it and loading it into the data warehouse.
Generally, none of the data that companies have comes by default in a form that is ready to use to solve the problems of your business. Without ETL processes, companies would find a large amount of data that they cannot use. There’s no doubt that to get on with ETL technology you need to find a service which will be professional in this sphere, such as Visual Flow.
However, you need to remember that an ELT data pipeline is a simplified pipeline. It allows you to load the data into the database in a simple way, since there are no transformations. In conventional ETL infrastructures, it is on data engineers (i.e. technical, non-business profiles) that all pipe construction and maintenance work is based. In an ELT infrastructure, it is analysts, data scientists, who transform the data stored in the databases. With an ELT infrastructure, it is analysts and more broadly business users who regain control of the data pipeline.
As you know, data pipeline solutions are more resilient, easier to evolve. The reason is simple: upstream transformations are not predetermined (in the pipeline design phase). Transformations are made after the data has joined the base in their raw form. Typically, the addition of a new data source does not require redesigning the pipeline and using data engineers. It’s the analysts who manage – and it can be managed in a fairly simple way!
What is the purpose of this process?
ETL is a powerful method that can work together with data management and integration tools to meet our company’s objectives. Some use cases include:
- Data migration from legacy systems with different data formats.
- Consolidation of data as a result of a business merger.
- Data collection and merging from external suppliers or partners.
- Work with metadata to allow data traceability.
In addition, you will get integration of new data sources such as social media, videos, devices connected to the internet of things, among others as well as self-service analytics to offer the possibility of making decisions based on data to business profiles and without technical knowledge.
Main benefits of ETL data pipelines solutions
In short, the main benefits that an ETL tool can provide to your company are:
- Allow extracting and consolidating data from multiple sources;
- Provide a deep historical context about our company and business.
It facilitates the analysis and reporting of data in a simple and efficient way, through visual representation. Moreover, these situations Increase productivity and facilitate teamwork and allow your business to adapt to the evolution of technologies and integrate new data sources with traditional ones.
It will definitely allow managers of your company to make strategic decisions based on data. It’s clear that ETL puts us in a position to be able to extract from them the knowledge that can help us solve our business problems and be true data driven companies.
What are the challenges of working with ETL?
ETL processes are essential for each company. However, they face important challenges that you have to overcome to adapt to new needs:
Real-time data processing. More and more decisions need to be made with greater speed, which contrasts with the batch operation of traditional ETL systems, which have to be adapted to operate as close as possible to real time.
Increase the speed of data processing. The increase in both the amount and complexity of the data sometimes makes transformation tasks difficult. In this sense, a nation the concept of ELT (Extract, Load and Transformation), which postpones the transformation last, is already being carried out in the destination system, and taking advantage of the computing power of the database engine.
Integration of new data sources. Currently, companies need to access all kinds of heterogeneous data sources: videos, social networks and even data generated by machines (Internet of Things). For this reason, ETL tools need to evolve and add new transformations to support these new data sources and those that will come in the future.
If we are talking about price, ELT data pipeline is less expensive because it is easier to maintain. This simplicity stems from the previous points. As we have seen, the role of data engineers in pipeline maintenance is reduced, which allows them to free up time for tasks with higher added value. In fact, the maintenance of the data pipeline (of the “Extraction” & “Loading” phases) is often outsourced and automated. An ELT allows the company to focus its efforts on what matters most: the transformation of data and, behind it, its exploitation into activation.
