What is the Signification of Open APIs in big data analytics? In recent times the term ‘Open Source’ has gained much favor in software and information technology. A decade or so back, this concept was in its infancy. However, with the rapid evolution of Cloud computing, Mobile Enterprise Application Platforms (MEO), and various other emerging technologies, open source has gained much importance in today’s software usage.
Today, an increasing number of businesses are choosing to use open-source programming technologies to deliver business applications. The primary reason for this is to reduce cost and control the data. In fact, many companies like ONPASSIVE find that going for open-source solutions reduces cost and control issues and allows them to make better choices regarding the data available through online resources.
As a rule, businesses that go for an open-source solution are perceived as more flexible and have a better IT infrastructure. The flexibility is brought about because these systems are easier to customize and easily integrate with other systems. On the other hand, an open-source system allows easy integration and support for common business concerns. This means that application developers do not have to rely on a single vendor for all the needs. Instead, they can use the right tools for the right job.
For instance, SAP has recently taken up the initiative of open-sourcing some of its big older data solutions. This initiative includes the re-vamping of its Analytics Business Intelligence tool and its BI-Stage product. The tool works in conjunction with the IBM WebSphere Information Integration (SIIA) and IBM Information Server (IIS).
With the re-vamped solutions, SAP will now deliver on-demand and cloud-based analytics to business users across its entire global territory. This move indicates that there is no sign of SAP lagging behind any of its competitors regarding innovation and transparency regarding big data analytics.
What is the Signification of Open APIs in Big Data Analytics? In general, any business decision made based on data provided by big data tools should be made based on solid business intelligence (BI) models. When these models are based on solid open-source frameworks, the enterprise can get much value out of it.
This will ensure that the business intelligence solution deployed is tightly coupled to the open-source platform and adjusted and tweaked to suit the evolving business environment. In essence, this ensures that the API model deployed is tightly coupled to the software stack used by the developer.
In addition, any big-data framework that is based on an open-source platform will allow for rapid evolution and enhancement. This is because the code that drives any such tool is typically readily available on the internet and can be easily pinned down and enhanced over time. With such a low cost of investment, a company like ONPASSIVE that decides to use big data analytics should also make the tool more responsive and adaptable as and when required. The result is that any such framework that is developed should be flexible enough to provide rapid and meaningful insights on the real-time information obtained using the analytics tool.
What is the Signification of Open APIs in Big Data Analytics? This brings us to the next question that many developers often ask: what is the contribution of open source to this development? The answer is simple: most of the big data tools today use a wide range of open-source tools to power their functionality.
This means that a wide range of software libraries have been developed over the years to make them run smoothly. This has ensured that integration possibilities are broad and that integration across multiple platforms is a possibility. The result is that there are now options for data sources from mobile devices, the internet, and even social networks.
Conclusion
The signification of Open APIs in Big Data Analytics is that open-source analytics tools are more flexible than their proprietary counterparts. It also ensures that the user does not pay additional costs for customization.
In the end, business-like ONPASSIVE will be able to take advantage of the full potential of big data applications across industries without paying exorbitant amounts to do so. So, the next time that you ask the question of the signification of open APIs in big data analytics is, you will know what to look out for and how to use them in your applications.
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