Businesses often rely on pieces of data coming from multiple sources, so they adopt ETL (extract, transform, and load) services that can process smaller, decentralized data stores, commonly referred to as data puddles. Data puddles are a practical starting point for managing information: easier to maintain, faster to access, and more adaptable to real-time business needs. However, this approach works well only in the early stages of the data collection.
It’s only a matter of time before you’ll need to generate data pieces and, thus, require more powerful ways to effectively process them. So, when the number of these data puddles grows, and you don’t adapt your system along the way, it can lead to operational chaos, resulting in low performance and financial loss due to excessive manual work.
Digital transformation becomes a necessity for stability, effectiveness, and growth. Businesses require efficient data pipeline services that can operate dynamically, scale without compromising performance, and integrate seamlessly with other data management tools. Cloud-based ETL services provide these benefits. Our recent telecom case shows how evolving a billing system from fragmented data puddles to a scalable cloud ETL setup eliminated performance bottlenecks and enabled smart, data-driven tariff management.
Given the shortage of technical specialists and the high cost of their work, cloud transformation is a wise investment, both financially and technologically. This decision pays off within a year by freeing up time and resources for existing staff and reducing the team’s workload for more strategic tasks.
Traditional ETL vs. Cloud ETL
Traditional ETL requires a heavy investment in hardware and IT teams, which is not an option for small businesses. Cloud ETL eliminates these costs and offers responsiveness to demand.
By using cloud-based services, platforms, and infrastructure, this approach ensures seamless and scalable movement of data across different environments, maintaining its quality, consistency, and accessibility.
All in all, cloud ETL is an excellent approach for growing businesses that rely on timely analytics and require simplified data integration from a mix of sources, all while automating transformations for analysis and business intelligence, and robotic process automation.
Types of Cloud ETL for Modern PaaS/IaaS: SAP, AWS, Azure Microsoft
Cloud storage apps have revolutionized how businesses handle and process large datasets in real time. Leading platforms allow access to more expandable, flexible, and efficient data pipeline services that can be customized to cater to modern business needs.
SAP
SAP offers several cloud-based ETL tools that integrate seamlessly with its ecosystem. SAP Data Services are older versions that have been foundational for a long time. SAP Data Intelligence and SAP HANA Cloud are newer options that have already transformed how data is processed. Thanks to the latter, businesses can transform and analyze data with minimal overhead while ensuring secure, upgradable integrations across on-premise and cloud environments.
AWS
Amazon Web Services (AWS) offers cloud services for scalability, most suitable for SaaS. AWS Glue, AWS’s primary service for data pipeline, offers serverless data integration and transformation, enabling businesses to automate and scale their ETL processes. AWS Lambda is used for serverless, event-driven ETL tasks, which include more lightweight data workloads.
Microsoft Azure
Microsoft Azure offers an all-encompassing set of modern solutions for designing cloud ETL that are most suitable for medium and large businesses, with seamless integration for .NET developers. Azure Data Factory is a widely used managed service that orchestrates cloud and hybrid data integration workflows. Another one is Azure Databricks, designed for big data, AI/ML-driven ETL. Azure Synapse Analytics combines data warehousing with big data processing for ETL and analytics.
The benefits of ETL services based on the cloud for businesses
- Increased efficiency and reduced costs;
- Optimized IT infrastructure;
- Access to applications from anywhere and on any device, thanks to the cloud environment;
- Easy application scalability to match business growth;
- High level of security and built-in data backup capabilities;
- Faster optimization time;
- Fast decision regarding the chart data;
- Price per Azure is cheaper than an employee, with speedier scalability.
Business scenarios that call for cloud-based ETL
Even small projects require efficient data engineering solutions, especially for small businesses, where resources are often limited. Cloud-based ETL is the go-to if your organization is:
- Adopting or expanding a data puddle approach for decentralized data management;
- Facing the need to integrate spanerse data sources into a unified pipeline for real-time access and processing;
- Preparing for business growth that demands a scalable data infrastructure;
- Aiming to boost operational efficiency while reducing costs;
- Seeking global access for seamless operations across locations;
- Needing a high level of security with robust data backup capabilities;
- Increasing availability and improving response times for more efficient operations.
NetLS’ expertise in app migration to cloud services
As part of our app migration to cloud services, we offer a complete cycle of the transition process, with the following crucial steps for successful cooperation:
- Application Assessment – identifying which apps are ready for migration and which require modifications or updates.
- Cloud Solution Selection – inspanidually defining the most suitable cloud provider for each client’s needs, along with the appropriate type of computing resources.
- Migration Strategy Development – designing a unique migration plan, including clearly outlined steps, technical requirements, and a timeline.
- Data and Application Migration – transferring data and apps from local servers or other infrastructures to a cloud platform.
- RPA (Robotic Process Automation) – identifying routine, rule-based business processes suitable for automation and implementing Robotic Process Automation tools to handle them efficiently.
- Testing and Optimization – ensuring correct and stable applications’ functioning and finding ways to enhance overall productivity if needed.
- Post-Migration Support and Maintenance – delivering optional support and maintenance services after the migration process for the reliability and effectiveness of cloud applications.
In the end, analyzing data with cloud apps becomes more streamlined. Take a look at the solution designed by our team described in one of our recent cases, Development of an effective ETL solution for efficient business management and the value it has brought to our client. We have established an effective ETL process for Data Puddle that allows for real-time analytics from information coming from multiple sources.
NetLS applies years of proven software development expertise to every project — explore our case studies to see the results in action. If you’re looking to improve data management and reduce operational costs, we are ready to help your business gain a technological edge at the most affordable price.