In the competitive digital marketing world, every business should use data accurately to get a sneak peek into their respective market, audience behavior, and business operations. The availability of the right data in hand can help organizations boost their business presence and inform the target customers about products and services effectively. The data generating in every organization is growing tremendously and demanding proper utilization to boost marketing efforts. Proper employment of marketing data can help businesses to ensure the success of their campaigns and bring higher ROI.
As per a report, nearly 60% of businesses are generating value with the use of data, and the numbers tend to increase in the coming future. Therefore, it becomes imperative for every organization to implement reliable data integration technology.
There are multiple processes you can use to consolidate your data, but the most popular ones are ETL and data warehousing. To help you choose between the two, here we are explaining both.
What is ETL?
ETL stands for Extract, Transform, and Load. There are different types of ETL tools available in the market, which you can use to effectively carry the ETL process. The process begins with data extraction from multiple sources like databases, clouds, and marketing platforms. Once the data is extracted, the same is transformed into a specific and easy-to-understand format. Lastly, the formatted data is loaded into the target destination from where it can be further used for analysis and reporting tasks.
The process of ETL plays a major role in outlining the data integration strategies. It helps businesses combine all their data from disparate sources into a single, centralized location to provide a vivid view of the market and business processes.
What is Data Warehousing?
Data warehousing involves the creation of a data warehouse and using the same for data storage and transformation. With data warehousing, you can store large volumes of data in a single place and transform it into a lucid format for effective utilization. It is an important component of business intelligence that assists data analysts in employing analytical techniques on business data.
In comparison with ETL, in data warehousing, the consolidated data is first loaded into the data warehouse, and then the transformation takes place. With the best data warehousing services, you can generate maximum value from the data available.
Difference between ETL and Data Warehousing
Both processes have equal importance when it comes to making the most out of the available data. They help you break the big data silos, combine data strewn over disparate systems, and get valuable insights to empower every business decision you make. But there are a few differences between the two that will help you find which data integration technology will work best for your business.
To help you out making the right choice, here we are listing the major differences between ETL and data warehousing:
- Data Transformation: With data warehousing, you get the freedom to transform a particular data set required at the moment. The level of flexibility helps you create diverse metrics and reports for different data types. Although creating different reports for different sets of data will slow down your analysis process a little bit. On the other hand, ETL transforms all the data in one single format before loading it into the data warehouse to add rockets to your analytics process.
- Existence: It’s been more than two decades since ETL has been serving the needs of the data-driven sector. There are highly advanced ETL tools available in the market that you can use to perform your data integration process like a pro. On the contrary, data warehousing is a new technology (in comparison to ETL) that offers unlimited scalability and cloud-based services.
- The search for data scientists: The ETL process is serving the needs of data-driven organizations for a long time, and that makes it a little easier to find experts having experience in handling ETL data pipelines. Whereas data warehousing, being a new technology, makes it a little harder to find experts that are well-versed with the process handling.
- Reliability: As organizations are using ETL for quite some time now, they find it a more reliable option to depend on for their data integration needs. On the other hand, data warehousing is a new technology having its systems and tools still in the evolving stage. This makes the technology a little less reliable when compared to ETL.
- Compatibility with data lakes: Data warehousing and data lakes are two terms highly associated with each other. Data lakes are the stores that allow you to store raw data. You can store any volume and complexity of data in data lakes without any hassle. In contrast, when using the ETL process, you must transform the data into a specific format before loading it into the target location.
- Hardware requirements: To perform the ETL process, you must be equipped with all the required hardware. In comparison, data warehousing is a cloud-based data integration solution that does not demand any special hardware.
- Implementation: With the help of the advanced ETL tools available, you can build a robust data pipeline. In addition to this, it will become easier for you to find data scientists with considerable experience in managing the ETL process. On the other hand, data warehousing technology is still evolving, and finding experts to implement such technology is challenging.
- Data Types: When it comes to dealing with complex, small data sets, no technology except ETL will work best for you. Data warehousing can be used when you need to transform large volumes of data in the least time possible.
- Task performance order: The ETL process begins with extracting data from diverse sources, transforming it, and then loading the transformed data into the target destination. On the other hand, the process of data warehousing starts with the aggregation of data from various sources, loading it into a preferred data warehouse, and transforming different sets of data into different formats as required.
Conclusion
We hope that the points mentioned above have helped you understand the major differences that ETL and data warehousing processes share. Both processes have their own importance and can be used according to your organization’s exact requirements. Apart from data integration, both technologies can help you in managing many other tasks that will save you loads of effort and time. As you have gained a precise understanding of ETL and data warehousing, it’s time for you to pick one and get going with meeting the demands of your data-driven business.
