What is Data Integration?
Data Integration is the way forward for businesses aiming to make waves in this era of digital innovation. Data integration brings together data from many different sources across the organization.
This pooling of data in a single location helps provide your enterprise with accurate, complete, and updated data for various organizational needs like data analysis, business intelligence, machine learning, application inputs, and other business processes.
The data integration process includes many aspects like data replication, data ingestion, and data transformation that combine different data sources into a standardized format for storage in a centralized repository like a data warehouse or data lake.
There are many approaches to data integration. However, the most popular approaches that are utilized by enterprises worldwide are as follows:
1. ETL Pipeline
The ETL pipeline is considered the traditional method. This data pipeline can convert raw data into the format recognized by the targeted data storage system. The ETL pipeline extracts, transforms, and loads the data into a repository—typically a data warehouse.
The ETL pipeline process allows for quick and precise data analysis within the data system. It is the best procedure for smaller datasets that require more complex transformations.
2. ELT Pipeline
The ELT method is more modern. This pipeline loads the data into the data storage system before transformation. The ELT pipeline approach is preferred in cases where datasets are large, and speed is necessary.
3. Data Streaming
This method takes a different approach to data integration. Unlike ELT or ETL, the data is not loaded into a new repository. Instead, the data is streamed from source to destination continuously.
Modern data integration systems can send data that is analytics-ready via streaming. Streamed data can be delivered directly to cloud platforms, data warehouses, and other repositories.
4. Application Integration (API)
Application integration is the most innovative approach to data integration. Using API allows for different, independent applications to work together in order to move and sync the data between them.
This is the best option for industries where data consistency is of prime importance. For example, your finance system and HR system should be in sync in order to manage payroll procedures.
Application integration is different from other methods of data integration. It is more geared towards sharing and syncing data between different applications. Meanwhile, data integration is concerned with centralizing the usage and storage of existing data from multiple sources.
Let’s take a look at how Application Integration differs from traditional data integration.
Traditional Data Integration vs. Application Integration: Major Differences
Being a modern adaptation of data integration, application integration operates differently from traditional methods like ELT or ETL. Let’s take a closer look at the key differences between API and Data Integration in the table below.
| Key Aspect | Application Integration | Data Integration |
|---|---|---|
| Focus of Integration | API is focused on connecting applications together, allowing them to communicate, cooperate, and exchange data effectively. | Data integration is focused on gathering data from multiple platforms and sources in order to create a consolidated dataset within a target repository like a data warehouse, data lake, etc. |
| Storage of Data | Data is maintained and stored within the individual applications. | The final dataset is stored in a centralized location. |
| Transfer Procedure | API merely uses middleware to act as a bridge between data sets of various independent applications. | Data integration transforms data from multiple sources into a format suitable for storage in the target repository. |
Key Concepts of Data Integration through No-code and Low-code Platforms
No-code and low-code data integration platforms
No-code and low-code platforms have drastically changed the way data integration takes place. As frontrunners of digital innovations, these platforms bring simplicity, flexibility, and speed to the process of data integration. Professional developers and civilian developers alike can utilize no-code and low-code platforms easily to facilitate efficient data integration.
Benefits
- Data management is simplified
- Reduces development time
- Allows diverse teams to collaborate effectively
Data Fabric
Data fabric takes data management to a whole new level. A data fabric is an architectural framework that uses advanced algorithms to process metadata. This allows for easy automation of data integration and preparation tasks.
Benefits
- Enhanced quality of data
- Simplicity in data handling
- Easier data analysis and research
- Useful for forming more reliable insights
Data Mesh
Data mesh treats data as a product. This architectural paradigm decentralizes data governance and ownership, allowing data users and producers to use data for easier collaboration. It is an effective method that allows for independent data analysis and encourages users to self-serve.
Benefits
- Promotes team collaboration
- Empowers domain users to work together
- Enhances insights and data analysis
The ROI of migrating your business to no-code platforms
1. Increased accuracy, efficiency, and productivity
Manual inputs can lead to errors. No-code platforms allow easy, automated migrations that require little to no manual inputs. This can eliminate process errors and reduce the time taken to complete tasks. With more time on their hands, employees can focus on tasks that provide value addition.
2. Streamlined workflow
Data integration makes it easier for users across the enterprise to access and utilize data. Combining data integration with application integration can allow for the data in your enterprise to migrate easily between applications and processes without loss of integrity. Maintaining data integrity is essential to improving coordination and decision-making.
3. Resource optimization
Eliminating data redundancy is a major aspect of improving efficiency. Data migration on no-code or low-code platforms can store data centrally in a repository that is easy to access. This can reduce the heavy burden on applications and users who have to retrieve data from multiple sources. By eliminating redundant and needless data, you can optimize the use of resources.
4. Cost reduction
With all your data migrated onto a single platform, you can eliminate the extra expenditures for multiple platforms. Centralized data can also be easier to manage, allowing for optimum use of your workforce and system resources.
JIFFY.ai: Data Integration through a no-code platform
Your business runs on multiple applications and software. This can lead to quite a lot of inefficiencies if traditional operational methodologies are followed. The common causes of inefficiency are as follows:
- Manual data entry on multiple platforms leads to a mismatch.
- Adopting new technology becomes difficult due to a lack of cross-platform support.
- Teams working on the same dataset in different applications are unable to migrate data between applications due to formatting issues.
- Complex processes requiring multiple formats for the same data
All of these issues can hold back your business from reaching its full potential. That’s where no-code platforms can swoop in to save the day with easy data integration.
JIFFY.ai is one of the best no-code platforms for data integration. With some simple steps, you can connect multiple applications and data formats together under one single platform. JIFFY.ai is equipped with a broad network of out-of-the-box integrations that can open doors to new possibilities.
Powered by AI, JIFFY.ai is able to automate these integrations swiftly, allowing for seamless workflows. Not only that, JIFFY.ai uses machine learning to determine shortfalls in data points and documents, catching mismatches and errors and helping to correct them quickly.
JIFFY.ai enables real-time information sharing, enabling your business to get the latest insights for quick and easy decision-making. If you are thinking of migrating your data onto a single no-code platform, JIFFY.ai is the right solution for all your data integration needs.
Contact us at JIFFY.ai to try out a free demo and get migrating.
