The importance of data integration
Data integration allows organizations to unify and analyze data from various sources, leading to better insights, informed decisions, and improved efficiency. It supports data-driven initiatives, enhances data quality, and drives innovation and growth.
One of the largest issues that data integration solves is the removal of data silos. Getting rid of data silos is essential for promoting collaboration, gaining a holistic view of the business, enabling advanced analytics, and ensuring data governance. By breaking down data silos, organizations can harness the full potential of their data, drive innovation, and achieve a competitive edge in today’s data-driven landscape.
Here are some benefits of removing data silos:
- Improved collaboration and communication among teams.
- Enhanced visibility and understanding of the business.
- Uncovering valuable insights and patterns through integrated data analysis.
- Facilitates advanced analytics and data-driven decision-making.
- Ensures data governance, security, and compliance.
Data pipelines in the modern business
Data pipelines play a crucial role in modern businesses by facilitating efficient and automated data flow from various sources to the desired destinations. A data pipeline is a series of processes and tools that extract, transform, and load (ETL) data, enabling organizations to collect, integrate, and analyze information in a streamlined manner. In short, data pipelines empower the flow of data through your organization, making it accessible when you need it.
In a modern business environment, it is crucial that data pipelines be constructed quickly and operate with high efficiency. This means that you need a well-defined development, deployment and maintenance plan.
Data pipelines and ETLs are often built haphazardly and without proper organisation. The speed at which the data is required often creates time constraints, forcing developers and implementation teams to deliver the minimum viable solution to a problem quickly. However, this impact is far-reaching and can result in poor data quality. This then poses a risk to the business as poor data quality can impact decision-making.
Lower the time and skill requirement with the right platform
Running a data team can be an expensive endeavor. You need a collection of tools, skilled developers, data analysts, business analysts and data owners. There are options available to manage this and to lower the skill and time requirement of your development, deployment and hosting efforts. Better yet you can select a single platform to take care of most of these activities.
Here are the benefits of using a specialised platform
- Accelerated development: These platforms usually offer prebuilt components such as data source connectors which then just needs basic configuration. Combined with a visual interface, the platforms allow developers and implementers to quickly assemble data integration workflows without writing extensive code. This results in faster development cycles for your data integration projects.
- Efficient debugging and testing: With built-in debugging and testing features, time spent on these tasks can be drastically reduced. Implementers can quickly see exactly where there is a data mapping problem or where a process breaks and can implement a fix accordingly.
- Easy deployment and application hosting: Specialised platforms usually have a single-click deployment process that eliminates the need for complex and time-consuming deployment processes. These platforms also come with a hosting server, meaning that you can quickly get your data pipelines live without worrying about infrastructure.
- Standardisation of data pipelines: By moving all data pipelines to a specialised platform, standardisation is automatically enforced, making support and enhancements efforts more manageable.
- Built-in scheduling and orchestration: Data loads can be scheduled to run at a specific time, or can be triggered by an event such as a file being dropped in a folder. These features are usually also available as pre-built components meaning you only need to add your configuration.
- Added development features: Specialised platforms can offer more than just ETL development; they can also offer solutions to data distribution such as automated file creation and delivery, API creation and hosting and logging.
- Reduced development costs: By streamlining the development process and reducing the reliance on extensive custom coding, a specialised platform can help lower development costs associated with data integrations. Platforms like Linx also promote reusability, meaning you can build once and reuse a specific workflow multiple times.
For example, the development team is at capacity and can not take on any additional projects at this time. There is an urgent report that needs to be developed and sent out to clients. The report needs to be sent every month end, meaning there will have to be some sort of automation. This can quickly be developed by using a platform like Linx. Users can set up data reads, file creation, email sending and orchestration. This process can be created and deployed by a business user.
Building data pipelines with Linx
Linx is a low-code integration platform that allows you to build bespoke and flexible back-end applications. By using pre-built connectors, you can read and write to any data source (database, file or API), automate any business, application or data process effectively manage field mappings and transformations and implement bespoke and flexible logic.
Orchestration can also be done in Linx, meaning that you can kick off processes based on a schedule or based on an event; for example, a file is dropped in a folder. This is ideal for loading files when they are available and sending reports at the end or start of the month.
After applications are built, they can be deployed with a single click, meaning there is no need for complicated deployment pipelines and processes. The application will also be hosted by a Linx server, which takes care of hosting, monitoring and error logging.