ETL Development: ETL, BI and Data Warehousing

There are a lot of ways to improve performance and make your business more efficient and, therefore, profitable using data integration and insight extraction. ETL is one of them. But what is it? When do you need to implement it? Our article will answer these and other questions regarding ETL development, so keep reading to discover more.

ETL development and ETL developer: definitions

As usual, we start with definitions. ETL stands for Extract, Transform, Load. It is a type of data integration which is used for blending data from numerous sources. ETL is frequently used for building a data warehouse, and the process involves three steps.

First of all, the data is extracted from a source system. Companies tend to keep the data across different software, so it has different formats and is stored in numerous sources. Therefore, during this stage, it is essential to define the required sources and format of data, and gather the information.

Secondly, the data is transformed into a suitable format. For instance, you implement ETL for your financial data, and the information collected is 65 cents, $12.42, 120 USD, and 05.45. After formatting, it should look something like this: $0.65, $12.42, $120 and $5.45. For this stage, the data is usually kept in temporary storage.

The third step is loading the data into a data warehouse or another system. By this stage, the data is already formatted and structured, but you will also have to decide what kind of database to use. If you are working with loads of information, we recommend to go for a data warehouse. If the amount of data is not that big, you can choose any database you want.

In turn, the ETL developer is a software engineer who covers the above-mentioned stages of the ETL process. His main responsibilities include:

• Managing the ETL process
• Data modeling
• Data warehouse architecture
• Developing ETL tools
• Testing

To deal with these tasks, an ETL developer needs to have the following skills and experience: software engineering and data analytics background, database architect background, experience in using ETL tools and scripting languages, problem-solving, organization.

You may also find it interesting – Data Warehouse Implementation

Other roles

Depending on the scope of your project, you may need some other experts to join your data engineering team and assist the ETL developer. Here are the roles you may need to cover:

• Data architect (projecting the infrastructure)
• Data analyst (defining methods of data collection and outlining the process of the data transformation)
• Business intelligence developer (developing business intelligence interfaces)
• Data Scientist or Software Engineer (especially required in case your project is related to machine learning)
• Database developer (modeling, developing and maintaining the data storage)
• Data engineer (developing interfaces for getting access to the data)
• A database administrator (managing the database, especially required in case you have several databases or if the database structure is too complex)

When can ETL be useful?

Data warehousing is one of the most popular fields of ETL application. However, there are some other areas where you can use ETL. Take a closer look:

Internet of Things data integration

Internet of Things has conquered the world, and nowadays there are numerous connected devices and systems available: smart security systems, wearable gadgets, and many others. If your business is somehow related to IoT, you can use ETL to collect data from various IoT sources and gather it in one place. In this way, it will be much easier for you to analyze this data.

Marketing data integration

Just like in the previous case, ETL can help to collect in one place all the marketing data you have. This process may involve marketing and customer data, web analytics, social networking data, etc.

Artificial intelligence and machine learning

Again, with the help of your data science team, you can move the data to a single place and prepare it for building a machine learning model.

Cloud migration

Cloud migration is moving your data from the premises to the cloud. ETL is a way to deal with this process. However, here is a little tip for you: to increase the security of your data, do not keep it only in the cloud storage. We recommend having the duplicate in your premises. This strategy can help you in case of a data breach and loss of information.

Database replication

You can use ETL to copy the data from your source databases to the cloud warehouse.

Apart from this, you may need ETL in case the volume of your data is constantly growing. An increasing number of data sources can also be a reason for implementing ETL. As a result, you will make your data more accurate and easier to understand. It will also be more convenient for you to integrate the data across diverse applications, and manage it.

ETL development as a part of Business Intelligence

Business intelligence (or BI) is another thing many companies are trying to implement nowadays to stay afloat, so we will devote a short paragraph exactly to it. The main mission of BI is to make your business decisions more informed and efficient. And to make the data required for these decisions actionable, it is easier to bring it to one place.

After you complete the stages of the ETL process, your business intelligence team can start running queries on the formatted, structured and uploaded data. The results are then shown to the individuals responsible for making business decisions. In this way, the entire BI process can be simplified and made more efficient.

By the way, if you would like to learn more about the best business intelligence practices, we have an informative page for you about Business Intelligence services.

ETL development partner

Nowadays, there are more than enough ETL tools available on the market, like Talend, Skyvia, SSIS, DataStage, and others. They have different features and prices (although some of them are still free to use), so you can try to find something suitable for your needs. However, finding an ETL partner can be a much better decision, especially in case you don’t have an experienced data engineering team. A proper partner will ensure that you have all the data management processes in place, and deal with all the potential issues.

Here are a few tips on how to find an ETL development partner. First of all, look for an entire data engineering team. There is no sense in hiring an ETL developer in one company, a data scientist — in another one, and a data architect — on a remote basis. Such a strategy will lead to issues with communication, while the project itself will get prolonged. So it is better to find a team of experts who have already been working with each other for some time.

Secondly, don’t be shy to ask the potential partner about their previous projects. Ideally, you should build a partnership with someone who has already completed similar tasks. For example, if you have a big and complex project, don’t hire a team that worked only with small amounts of data.

Thirdly, consider your time zone and language. The language barrier and huge differences in schedule can result in serious issues with communication. And, finally, stay in touch with your partner throughout every stage of the ETL process.

To sum up

So, now you know what ETL is and how to make this process possible and smooth. But if you need some assistance or answers to other important questions (for instance, regarding ETL and data science services or ETL for machine learning), you are always welcome to get in touch with us.