(Sponsored) The vast majority of today’s data was only recently created. You will be surprised to find out that more than 2.5 quintillion bytes of new information is created daily. The amount of data generated per minute is impressive. Today, accurate data is absolutely necessary for a smooth business. It will remain a key factor to business success for a really long time from now on. However, more important for businesses all around the world is how they process the data they have.
However, before discussing the importance and benefits of ETL Data Integration tools, we should first acquire more information on big data. We should understand the topic better.
Big Data – What Is It?
Searching for a definition of big data online will usually leave you with plenty of different versions of it. However, for now, we will resume our assessments and presumptions to the definition according to which big data is raw, unprocessed information. Over the past few years, we became able to use more effectively this type of information because we all realized how this type of data could change the way we live and most importantly, the way we work and change to the core the way we think. If you consider all the data that businesses today own, it’s amazing how these can become increasingly profitable by using it. And this is why we pay increased attention to big data today.
On the other hand, simply having impressive amounts of raw, unprocessed data won’t help businesses very much. Being able to structure, analyze and interpret data is by far more important. Only this kind of data is relevant and important for businesses. This type of data offers business owner a more accurate insight into their establishments and the market as a whole. The classic ETL was unable to structure and organize data successfully. This made it impossible to use, in spite of its immense potential. This is how ETL developers began to bring improvements to their products in such a fashion to make analysis and proper use of information more successful.
ETL – A History Based on Evolution
ETL – an abbreviation for Extract-Transform-Load – was invented to ease the development of data warehouse and thus, to make those more useful and enjoyable. Over time, these tools have expanded their functionality and data profiling capabilities. Besides, they have improved their data cleansing abilities and big data processing. Other advantages offered by ETL tools are data management and data governance. When data is available in a data warehouse or an OLAP (online analytical processing) cube, BI software products are commonly used to analyze and use them. BI software products also bring their fair contribution to data discovery, data mining and dashboarding.
Data warehouse and ETL are two other notions we should dive in deeper. These two acquired over the years different understandings and have evolved quite a lot. However, the most common definition for data warehousing is “a system that extracts, cleans, conforms and delivers source data into a designated storage to be used for queries and analysis”. The main goal of data warehousing is to deliver reliable and highly accurate information so it can be used in the business decision-making process.
On the other hand, ETL tools help by extracting and copying data into the data warehouse. These tools, as you can tell from the abbreviation, simply pull data from one or more databases and place them into a single database which is simply called target-storage.
So, How Does the ETL Process Work?
ETL tools work on three fundamental principles at once: they extract data, transform data and load it into a target-storage.
- Extract – in the extraction process data from multiple sources and databases is prepared for the next steps. The fundamental goal of this step is to retrieve all the necessary data from multiple sources, with as little resources as possible. This step is designed in such a fashion that it doesn’t impact in any negative way the source system. Performance and response-time-wise, the source system remains the same.
- Transform – in this step, a set of rules is applied and these rules transform the data from the source to the target. This step usually converts the data to the same dimension, by using the same units. This allows all the data to be later joined together.
- Load – during this step, it is necessary to ensure that the load is performed correctly and that there are used as little resources as possible. This step practically writes all the data into the target-source.
Now that we have a clear idea on how ETL tools work, we should see what are the benefits of these tools.
The Benefits of ETL Data Integration Tools
The main advantage offered by such tools is that the whole process becomes significantly easier and faster than it is in other tools’ case.
These tools are easier to use and faster than traditional methods. Those traditional methods usually involve moving data by manually writing codes. ETL tools, however, contain an interface that speeds up the process significantly and extracts, transform and load data between sources with higher rates of accuracy. Below is a short list of some of the most obvious advantages offered by ETL data integration tools.
- Automation. ETL tools offer high levels of automation and the ease of use that usually comes with it. After choosing the data sources, the system automatically identifies different types and data formats, sets the rules for the extraction and processing and automatically transfers it to the target-source.
- Visual Flow. These systems are based on graphic user interface and offer a clear visual flow of the system on which it functions. This makes it significantly easier for the user to visualize the whole process and logic behind it.
- Operational Resilience. Traditionally, data warehouses are fragile and sensitive during operational processes. On the other hand, ETL data integration tools have built-in error handling capabilities and functions which allow data engineers to build a well-instrumented ETL process.
- Complex Data Management Capabilities. If you want to move around big volumes of data, then ETL tools are just perfect for this purpose. Even if there appear complex rules and transformations, ETL data integration tools simplify the process and assist the entire data analysis process. They also bring an enormous contribution to string manipulation, data integration and changes and creating multiple data sets.
- Advanced Data Profiling and Cleansing. The advanced functions offered by such tools allow complex data warehouse management and transformation.
- High ROI. ETL tools allow businesses to save costs and this way, they turn into highly profitable investments. A recent study showed that ETL implementation offers a 5-years ROI of 112%.
- Improved Performance. ETL tools work amazingly in building a high-quality data warehouse. They also come with improved performance-enhancing technologies. This way, they can deal and process higher volumes of data more effectively than other traditional data processing solutions.
The benefits offered by ETL data integration tools are numerous. Data processing becomes significantly easier in their presence and that allow companies of all sizes to effectively used the data gathered over the years. Only in their presence, big data becomes useful and can contribute to generating higher revenue.