What does “ETL” stand for?
The letters ETL stand for "Extract, Transform, and Load." In the ETL process, data is taken from different source systems, merged as needed, changed according to business rules that have already been set, and then loaded into the target system.
A Data Warehousing Institute study found that organizations that invest in ETL could see an ROI of up to 300%. ETL helps turn data that is not organized into organized data that can then be used for analysis.
Though it's important to note that modern big data technologies, such as Grow’s business dashboard software, already have a built-in way to structure data, so the ETL process becomes a part of it.
Here is an overview of Grow Transforms.
What does "Data Preparation" mean?
Data preparation, also called "wrangling" the data, is the process of getting the data ready for analysis and reporting. A data preparation tool is similar to ETL, but you don't have to be an IT expert in using it. Most of the time, these tools have a self-service, visual, and easy-to-use interface that business users can use to prepare data with little or no training and minimal help from the IT team. It helps clean up and organize all the messy and complicated datasets so that they are easier to use and can be analyzed faster. Data preparation is more critical than ever because organizations have a lot of data that is only getting bigger quickly.
A Gartner study found that organizations that invest in data preparation can save as much as 50% of the time and resources that would otherwise be spent on data cleaning and integration.
The main steps in preparing data are:
- Find and evaluate data.
- Change the data using granularity, temporality, and structure manipulation.
- Using clean data for business so it can be used for data analysis and visualization.
ETL or Data Preparation-What's Different?
Even though the definitions of data preparation and ETL may make them sound the same, there are some key differences between the two:
#1 ETL vs. Data Preparation: Who is the program for?
ETL tools are for IT professionals, while data preparation tools are for business analysts. The idea behind data preparation tools is that analysts, who know data the best, should also be the ones to prepare it. Organizations can't expect to get accurate analytics if only a few highly skilled employees prepare the data.
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#2 ETL vs. Data Preparation: Processes based on Mapping vs. Visualization
ETL tools are made to help IT teams handle well-defined processes for data cleaning and business intelligence. But because these processes are based on maps, it is hard to manage iterative and flexible data preparation and exploration.
On the other hand, machine learning and HCI (human-computer interaction) power data wrangling or data preparation, letting business users explore and prepare data without problems. Data preparation solutions also offer powerful visualizations that make it easier for users to find hidden patterns in data and make sound business decisions.
#3 ETL vs. Data Preparation: Help for data that is hard to understand
As the amount and complexity of data grow, we need more advanced tools to keep up with the growing complexity. The only way for an ETL system to work is if your data is organized, updated regularly, and based on batches. If you can't change the system with custom programming, ETL systems fail when dealing with time-sensitive streaming data. But even after tweaks, it can be challenging for an ETL system to keep both a high level of availability and a low level of latency.
Even though many commercially available ETL tools can handle complex data, the data must be made usable before it can be loaded. This means that the learning curve is longer and more processes must be implemented. Also, it's important to remember that ETL technology was never meant for business analysts. It was made for IT professionals.
Key Takeaways-
Grow with in-built ETL and Data Preparation tools
There are clear differences between ETL and data preparation tools, but the best for your business depends on its needs and the end users.
Data preparation tools can not only handle complex data without any extra tweaks, but they are also easy to learn and use, so business users can easily prepare and analyze data.
Even though ETL is an old technology, that doesn't mean you should get rid of it and start using data preparation instead. Instead, you should figure out how to move your legacy system to successfully integrate data preparation tools and decide where ETL tools fit in this new landscape. One of the most preferred Business Intelligence software vendors for that is Grow. Clearly, you don’t need to choose between ETL and data preparation when it comes to Grow, offering the best Business Intelligence software.
Contact Grow and unlock the potential of your business data.
