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Over-reliance on technical solutions that are hard to access or modify for business purpose puts an organization behind the competition. That is why the popularity of self-service integration has risen so much over recent years.
What is Self Service Integration?
Self-service integration reduces IT-dependency by helping data and business analysts to prepare and integrate their own data without much involvement of IT. Unlike a traditional BI environment, where the data coming from various resources need to be organized, prepared, stored, and secured for business use, self-service integration takes data in the form your clients, have it and transforms it into the form that business systems require. This is possible as most of the data formats and protocols come supported.
The big advantage of Self Service Integration
- It enables users of different tools to set up their own data mapping to cater to the business need.
- As a result, some of the key challenges faced by organizations and users in the line of business get resolved. These include — delays in revenues, data discrepancies, and reliance on IT for data onboard management.
- Companies can rethink their integration strategy and make use of data by opening data accessibility for all integration personas.
- Extracting data from heterogeneous tools to a common platform provides collaboration across the organization for a greater objective
Most important of all, self-service integration helps to break down the wall of “One Version of Truth” between IT and business— a critical driving force behind a business growth.
Breaking down the “One Version of Truth” or the vertical approach
This might seem like a contradictory statement considering that data should be consistent without any ambiguity. It should be capable of eliminating other alternatives that might arise through inefficiency in systems and processes used for data collection and management.
If we look in to a process-oriented approach, we might be able to compare the “One Version of Truth” to a vertical-oriented approach. In a vertical-oriented approach, data coming from countless sources converge to a single definition so that all business departments can align around the same definition of crucial terms. It might have turned out to be a successful exercise, except that some of these sources end up misleading during business decision making.
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The need of horizontal alignment for data traceability
This is exactly what self-service integration does not do. With self-service integration, your organization’s data pool follows a sideways communication along with bottom-up approach. A crucial factor for businesses having a shared understanding and a shared feeling of responsibility. A horizontal aligned approach enables a single point of view to be seen in multiple ways that are specific to the needs of individual departments.
Kovair Omnibus for Self-Service Integration between different ALM tools
Kovair’s Omnibus Integration Platform enables seamless data integration and execution across different ALM tools that include even homegrown proprietary tools. As a result, you get a holistic solution right from customer initiation to production deployment and feedback. In addition, data gets successfully parsed across different tools that are useful differently in different departments.
To give you a more simplified understanding, let us consider a scenario where an organization uses Jama Contour for Requirement Management, HP ALM for Test Management, and Bugzilla for Defect Management. With Kovair Omnibus as the middleware, when a requirement is reviewed and approved inside the Jama Contour tool, it automatically creates a Test Requirement inside the HP ALM tool. Likewise, when a test execution fails inside HP ALM tool, it automatically creates a Defect inside Bugzilla tool.
From the above example, you can now decipher how the same data in one tool (for example Requirement in Jama Contour tool) can leave a different insight in another tool (for example – Test Requirement in HP ALM tool).
Kovair REST API in Self-Service Integration
Kovair REST API enables end users to configure Omnibus platform using custom script or external application. This gives end users the complete power of extracting transactional data and data summary to external applications without involving IT.
With Kovair API and Omnibus platform, end users can directly approach for data query from multi-vendor tools. The same can be exported into an external application for business purpose. Similarly, data from external systems can be directly pushed into ALM tools like Jama, IBM RDNG, Bugzilla, etc.
Conclusion
Data utilization varies. It depends on how different departments in an organization use it. With self-service integration system, you can pay attention to how a single data can matter differently for different departments within an organization. Kovair has recently introduced a new product for Large Data Storage and Analytics called the ‘Kovair Data Lake’ and this will enable the readers to learn more about extraction, storage, mapping, and analytics of this data from multiple tools in large organizations. Kovair API enables external applications like BI tools to query data from Data Lake. This can then be used for further business analysis. Moreover, using API, external applications cannot just view the pre-defined data models but also query on the each of the models.
To learn more about Self-Service integrations with Kovair Omnibus and the Data Lake capabilities, visit the Kovair website www.kovair.com or write to sales@kovair.com today.
