ETL Data Integration: All you need to know

Marketing is everywhere and is affecting everyone. The data it creates is everywhere as well. You will find the data on various platforms in huge amounts and is gathered through an ever-increasing number of applications and tools. Additionally, data is constantly changing. For marketers, an exponential rise in data can seem to be a challenge for lifetime.
Gathering it, cleaning it, storing it together, and deriving sense out of it to obtain business insights can be overwhelming. Despite that, companies that master the entire procedure will be the ones setting themselves apart from their contemporaries. So, how can you be one of them? Well, through ETL data integration.
So, What Is ETL?
ETL is a kind of data integration and is an abbreviation for extract, transform, load – a 3-step process. It is the foundation of data-driven marketing and separates the analysis bit from everything that precedes it.
1. Extracting data is about getting it from a specific source and performing it in a way that every relevant information is obtained. For ETL to work efficiently, data should come directly from its source as well as in its rawest form.
2. Data transformation means stripping the data of its several formats, cleaning it, and harmonizing it. Put differently, it should become convenient for end user to read. It is important to ensure that the highest possible quality of data is acquired during this process, including finding and eliminating duplicates and filtering the data into predetermined, relevant categories.
3. The last step of ETL data integration is to help harmonize the data and load the data into a target location that essentially is a database or BI (business intelligence) tool of choice. Then, the data becomes ready for analysis.
Benefits Of ETL Data Integration
· Saves time – ETL enables an organization to collect, transform, and arrange data in an automated way, thus saving time and effort of doing everything manually. So, the times when rows of data needed to be imported and analyzed manually are now gone.
· Handling complex data becomes easier – The data a company works with is varied and complex. To begin with, it may include various currencies, campaign names, and timestamps. Apart from that, location coordinates, device IDs, customers’ names, time zones, and seller URLs are also present. Assembling this data would require immense work and through ETL data integration, it becomes easier.
· Better decision-making – Through automating critical data processes and decreasing chances of error to almost nil, you ensure that the data you obtain to analyze is of top-notch quality, which implies making robust business decisions.
· Reduced human error – No matter how efficient an employee is with handling data, they cannot be immune to committing mistakes. And an error in the initial stages of data analytics procedure can be critical. A single mistake would result in another one and so on. However, ETL tools will help you avoid that.
· Higher ROI – If you save time, resources, and effort, ETL helps to boost ROI in the future. Another benefit is that ETL data integration can help you acquire stronger and better insights.
Applications Of ETL
· Traditional uses – Many organizations rely on ETL every day like retailers who have to see their sales regularly. ETL can combine as well as surface transaction data from data store or warehouse so that it is ready to be viewed in a comprehensible format.
· ETL and Big Data – Having access to data gives the business a competitive edge. But businesses now need access to all kinds of Big Data, including social media, videos, spatial data, server logs, etc. ETL vendors often add new transformations to the tools for supporting these emerging needs as well as new data sources.
· ETL and metadata – Through metadata, businesses understand where does the data come from as well as its impact on data assets in the business. As data architecture turns more complex, it is necessary to track how the varying data elements in your company are used and related.
Conclusion
Due to the ever-increasing amount of data, adopting effective ways to transform Big Data into understandable information has become important. By extracting useful data, transforming it into a readable format, and then loading it into the target location, an organization can benefit a lot.