5 aspects of data integration platform design
Most mid-sized and large enterprises have their data scattered and isolated in myriad systems instead of an integrated solution. In today’s highly competitive business world, the tiniest pieces of information can become a game-changer. That’s why data integration platform design and deployment plays a crucial role in the success of an organization.
The integration of data enables better and compressed availability of information for various business processes and different departments. It allows companies to merge multiple data types and comprehend how it is relevant to the current business scenario. For instance, marketers collect customer data from several social media and other platforms, including Twitter, Facebook, Google Ads, etc. The data helps them make informed decisions about the wants, needs, complaints and pain points of their target audience. They get the leverage they need to create impactful marketing campaigns that drive conversions and sales.
However, the challenge here is acquiring or designing the right data integration platform. It is crucial to find out the critical elements before investing in a platform meant to handle all kinds of enterprise data. Unfortunately, most businesses struggle due to a missing feature or a complicated interface.
Read along if you’re considering investing in a data integration platform design and development.
Use of data integration platforms: the benefits
Lowered risk of errors
The scope of errors is unlikely with automation. However, manually carrying out tasks leaves room for errors. That’s where the development of a data integration platform comes in handy. Even if your business already has specific apps or software for specific processes and functions, it won’t guarantee data accuracy. A data integration platform ensures all the information is in a single place, and businesses can access that sensitive information in real-time.
Saves a lot of effort and time
Integrating data manually from various sources is a time-consuming process, and it can take your team hours to complete the task. With the help of a data integration platform, your team wouldn’t need to perform the job manually. Instead, they can use the readily available tools to integrate all the information quickly and efficiently and leave no room for errors.
When you have access to a robust data integration platform, crucial business information can be accessed without much effort. Furthermore, the efforts of your team of data analysts can be greatly reduced so they can concentrate on other aspects of the business, such as profitability.
The fundamental function of a data integration platform is to simplify complex data. The platform is typically responsible for aggregating semi-structured and unstructured data from various sources. Unless all the collected data is integrated and streamlined, businesses cannot use them efficiently.
Undoubtedly, there are tons of data available for collection today. But not all of the data is usable. As a result, businesses need to sift through tons of complex and big data to find what they need. This monumental task is made more accessible with the help of data integration tools. These tools can move data onto a single platform where your team can perform analysis and convert the collected data into something meaningful.
With the help of a centralized view of your data, making the best business decisions becomes easy, and you can utilize your organisation’s capabilities to the fullest.
Data integration leads to better collaboration between trading partners and employees. In addition, the automatic flow of data can positively impact your business and reduce the chances of misinterpretations.
Integrity of data
A data integration platform ensures the consistency, accuracy and completeness of data. Since data plays a vital role in the business sector, it is not feasible for businesses to receive false or incomplete information. Decisions based on incorrect data results in huge losses.
Elements of a data integration platform design
1. Data virtualization
Data virtualization is one of the approaches to data management that allows an app to retrieve and manipulate information without the technical details about the data.
When developing a data integration platform, ensure that the platform supports data virtualization. It must be capable of federating multiple data sources in real-time to offer end-users a unified view without the data being removed from its source.
Data virtualization has advantages when businesses need to view data in real-time or when there are business or regulatory reasons limit the copying of the information. However, it is vital to comprehend the limitations in terms of transforming data in real-time when the data is being federated. Also, you need to understand the performance impacts of these data transformations as they become complex.
It is possible to combine a data warehouse, data marts and a data lake with your data management projects. Each may have differing requirements related to data in the environment, what data temporarily passes through the environment and what data is acquired in real-time from secondary sources. Getting a grasp on this will help you create a better data integration platform and understand your requirements for data virtualization.
2. Flexibility and scalability
When it comes to managing data, data integration and scalability are the two issues on top of the list. Large enterprises need to handle massive quantities of data, both external and internal. As you must be aware, the flow of data within a company may change from time to time. Therefore, you need a high-performing, robust system that quickly scales according to the changing data requirements. In addition, the platform must be flexible enough to adapt to the evolving processing requirements of extensive information and data. If you have a scalable and flexible data integration platform, the limits from your organisation’s present and future volume of data will be removed. The platform will be capable of adjusting according to the changing data collection and integration requirements.
3. In-built job scheduler
For large organizations, information pours in from various external and internal sources. In an organization, the data flow doesn’t cease. That’s why your data integration platform design needs an in-built job scheduler. Automation will ensure that the data access through different business processes will remain uninterrupted.
An in-built job scheduler within your data integration platform will allow your organization to automate and schedule everything, from the execution of complicated workflows to simple data transformations. Automation will remove the hassle of performing tedious, monotonous tasks of performing regular backups, saving the invoice information of customers, revising employee information, updating inventory, etc. Due to this, companies can decrease their development and IT expenses while augmenting operational efficiency.
4. Compatibility to use data from unconventional sources
The ability to integrate data, along with transforming and leveraging it, is one of the most vital features of an effective data integration system. Of course, your data integration platform must support standard file formats: PDF, SQL Server, etc. But that’s not all. Since data is pouring from different channels, businesses must support unconventional source systems. If not, your analysis will have gaps, and the data will lose its meaning.
For an efficient data integration platform, you must ensure the platform is compatible with various unconventional data sources, including EDI file formats, COBOL file formats, XML/JSON files and email sources. In addition, it would be even better if your platform’s design integrates with Oracle, SAP HANA and other database platforms that popular among businesses.
5. Easy-to-use functions
What’s the use of developing a data integration platform that is too complicated to use? For making the best use of a data integration platform, ensure the platform is user-friendly and comes with easy-to-use functions. Moreover, the end-users must not take additional training to use the platform.
While the elements of a data integration platform design and development mentioned above are not all-encompassing, these are the crucial features that organizations cannot leave out. Besides these, it is advisable to conduct thorough research and find the features that work best for your business.