It’s impossible to imagine the gargantuan amounts of data companies amass. Indeed, they collect enormous volumes of information from various data sources and need the ability to get actionable insights in near real-time. The problem with getting different types of data from different sources is that it creates data silos, preventing the easy use and flow of data.
Data integration is a central process in business intelligence. It enables companies to transform data and initiate analytics and other data projects. In this article, we’ll talk about ETL tools and how they can help your company enhance its business intelligence processes.
What is ETL?
Extract, transform, load (ETL) is one of the most popular and trusted data integration strategies. As the name suggests, it involves extracting data from different source systems, transforming it, and loading it onto a destination system. The destination system can be a data warehouse or a centralized database that different applications share.
ETL integration can be time-consuming, depending on the volume of data involved in the process. There are many use cases for ETL processes. Those cases include creating data marts, building data warehouses, and integrating legacy systems.
What are ETL tools?
ETL tools are mediators that facilitate ETL processes. So, what is ETL tools‘ purpose? Their purpose is to provide a medium by which data engineers can extract and transform data.
There are many ETL vendors, so choosing the right ETL tools requires some homework. TIBCO is one of the leaders in data integration and ETL solutions. They create enterprise-level data integration tools and even provide affordable ETL software licenses for college students in tech fields as part of their mission to groom the data scientists of tomorrow.
ETL processes are manual. However, choosing the right tools makes data extraction, data cleansing, and data migration easier. Data scientists and business users need ETL tools with a staging area designed for ease of use.
What are the benefits of using ETL tools?
One of the biggest benefits of using ETL tools is that they enable you to maximize your use of big data. You can program your ETL platform to extract data based on changes, or you can initiate full data extractions. Moreover, you can create business rules for your master data and catalogs for your metadata.
You can also create a data store to house data for future projects. The data will already be structured when you need it, simplifying your data governance operations. ETL processes require a lot of collaboration between data scientists and business users, but a well-planned ETL strategy works like a well-orchestrated symphony. You’re the maestro, your data scientists are your instrumentalists, and their instruments—ETL tools.
What are the challenges of ETL processes?
As beneficial as ETL tools and processes are, there are also drawbacks and challenges. The main challenge with ETL integrations is they’re labor-intensive and prone to human error. As mentioned before, these processes require a unified team working in concert toward a common goal. Any lapse in communication is a chink in the armor of your integration processes and could hurt data integrity.
Integrating data from disparate sources is one of the most critical data functions. Data transformation enables companies to create data pipelines through which information can flow, powering quicker and better business decisions.
ETL is one of the most effective data integration strategies. It enables companies to create data warehouses for future analytics projects and format unstructured data into a single language, promoting efficiency and scalability. With the right ETL tools, you can maximize your business intelligence insights and gain a competitive edge over the rest of your market. So, what’s left to analyze? Start integrating your data via ETL processes.
