Crucial for effective data analytics is the accessibility of data that has been collected and depending on which data loading method you use, there are opportunities to not only significantly speed up your time to analytics and insights but also to dramatically improve overall data quality and accuracy.
As data is likely to come from a number of sources, in a variety of forms, ETL (Extract, Transform, Load) is often an efficient method of gathering data from across an organization and ensure it is fit for purpose before any analysis commences.
The Load element of ETL is what data loading refers to – once data is retrieved and combined from multiple sources (extracted), formatted and cleaned (transformed) it is then ready to be loaded into your chosen storage system.
Data is the lifeblood of organizations, allowing us all to make more informed, faster business decisions. Ideally, your ETL needs to be scalable and streamlined to provide the best results. Use ETL in your data integration process to help standardize your diverse data types and make it available for manipulation to meet the variety of demands from around your organization.
Benefits of Data Loading
Before the benefits of ETL had been realized and it had reached its current, evolved state – organizations were often forced to load data manually or use several different ETL vendors for each source of data! The good news is that today, the ETL process, which includes data loading, is designed for speed, efficiency, and flexibility.
Crucially, the ETL we have currently is also scalable and can meet growing data demands, it can handle any types and structures of data, and accommodates many data sources from IoT to connected devices.
Methods and Tools for Data Loading
As data loading is part of the entire ETL process, it is beneficial to any organization to have a solid understanding of the ETL tools and methodologies available, and which work best with their budget and requirements.
A few options include:
Open source. Many open-source ETL tools are quite cost-effective as their code base is publicly accessible, modifiable, and shareable – these tools can still require some customization or hand-coding.
Cloud-based ETL tools in the cloud are built for speed and scalability, and often enable real-time data processing. They also include the ready-made infrastructure and expertise of the vendor, who can advise on best practices for each organization’s unique setup and needs.
Batch processing ETL tools that work off batch processing move data at the same scheduled time every day or week. It works best for large volumes of data and for organizations that don’t necessarily need real-time access to their data.
Ultimately, businesses need data solutions that match the power and volume of their own data demands. A perfect match in this scenario ultimately allows any business to make informed, faster decisions to stay competitive, improve efficiencies, increase profits and excel in customer care.
Ready to get your own ETL started? As part of your ETL project, why not take advantage of our data quality tool called iData, to rapidly transform your data quality results
iData delivers:
Ready to discover iData?
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