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Today, we are living in a time when information is growing at an astounding rate. Managing this information effectively in order to derive useful insights from it is a challenge organizations are facing today. While data management has emerged as a universal challenge that is affecting organizations across every sector, the industries that focus on intensive scientific research are the ones for whom this acts as the biggest challenge. These industries, which include pharmaceuticals, chemical manufacturing and healthcare, can benefit immensely with the application of semantic search – the technology that has the power to turn unstructured data into structured data and fetch the most accurate and relevant results. ResearchNet is one such platform for researchers that is powered by 3RDi Search – a semantic search based platform.

1] To Enhance Possibilities of Early Phase Research

The use of semantic search technology can help bio-medical researchers stumble upon potential biomarkers and drug targets which they had no knowledge of earlier. This is possible because semantics enhances the scope of search. The insights thus gained can be used to formulate initial results prior to conducting lab testing.

2] To Get a Better Understanding of the Competition

When you are armed with a technology that allows you to find more and more information, you can use it to get a deeper understanding of the market trends as well as what your competitors have worked upon, including their patent filings. The technology can also be used to study non-patent literature in order to gain complete understanding. This helps organizations to get a clear picture of what patents have been already filed for and the work that is currently being carried out in the industry, which can be useful for purposes like patent landscaping.

3] More Effective Monitoring of Medical Literature

Since semantic search makes information retrieval quick and accurate, it can be used to make the process of monitoring medical literature – known as pharmacovigilance – more precise. With the use of semantic technology, it is possible to delve deep and discover how adverse events can ve related to pharmacological substances. Overall, the efficiency of managing workflows improves drastically with the implementation of semantic search.

4] Makes it Simple to Discover Chemical Compounds

As discussed earlier, semantic search is what organizations need to retrieve information from a wide range of sources, including journals, scientific papers, medical archives and more. This ease of finding information makes it possible for researchers to find more information in less time and learn about chemicals, drugs and other scientific substances using well-established ontologies.

5] To Enhance the Productivity of Researchers

The use of semantic search leads to a boost in the productivity of researchers working on a project. As we have seen earlier in the article, semantic search is highly relevant. Not just that, these tools work real fast tp produce the accurate results that the researchers seek. This makes the research process faster, which in turn leads to a boost in productivity.

The capabilities of semantic search tools provide a lot of benefits to researchers and the research intensive industries. Also, this is just the beginning as semantic search still has a long way to go and the future holds way more possibilities.

The software development industry has been witnessing a major change since the past few years with the introduction of technologies like DevOps, Agile and more. The advent of new technology has resulted in a major shift in the way we approach software testing. In fact, the software testing scenario has come a long way in the last decade or so and the future holds a lot more possibilities. This article takes a quick look at the top 5 upcoming trends in the world of software testing services so that the testers today get to know what the near future has in store.

Introduction of Machine Learning & AI to Testing

Experts in the field of software testing unanimously believe that artificial intelligence (AI) and machine learning are the two technologies that are all set to take the world of software testing services by storm in the near future. Today, we have both these technologies in their nascent stages but this is sure going to change in the next few years. This is because they can add an all new dimension to the technology of automation testing as we know it today, making it more effective. The future holds immense possibilities for the growth of both AI and machine learning as these technologies are what we need to evolve our approach to testing as software becomes more sophisticated and complex with every passing day.

Rapid Rise of Automation Testing

Automation is the current buzz word in the field of software testing services and experts predict that this is something that’s not going to change anytime soon. The future will see QA teams automate more and more. There will be a growing need for effective test automation tools like QARA Enterprise, Watir, Katalon Studio and the likes, which shall also evolve with the changing needs of the software testing industry. Interestingly, experts are also of the opinion that in spite of the increased use of automation, there will still be a need for manual testing, especially when it comes to testing parameters related to the user experience offered by an application. The challenge for testers would be to strike the right balance between automation and manual testing in order to maximize the overall efficiency.

Agile Under the Spotlight

It has been 17 years since Agile technology was first introduced to the process of software development and testing and it is predicted to have a bigger impact in the years to come. Agile technology promotes the concept of continuous testing and collaboration between different teams working on a project. This concept works towards the improvement of every phase, right from planning to execution. There are many benefits of going Agile which has made most organizations embrace the technology, and the future will be no different.

Big Data Testing

Big Data is a reality with the volume of organizational data growing by leaps and bounds. This ever increasing volume of data is a challenge that organizations are facing today. In the future, Big Data will also have its impact on testing and QA teams will have to change their approach in order to deal with it successfully. This is where the process of Big Data Testing comes into the picture as the solution that organizations seek, because the conventional approaches to testing won’t work for Big Data.

Increased Focus on Integration

The highly competitive market and the increasing need to deliver high quality products in the shortest time. This narrow timeframe has made it necessary to integrate the many elements of product development. Processes like requirement management and task management are carried out on different systems, which makes consolidation and analysis of data a time consuming process. Integration of various systems is an approach that can go a long way in saving valuable time and make faster time-to-market a reality.

Conclusion

The future of software testing services looks promising with several new technologies that are all set to make the task easier, faster and less complex for the QA team of tomorrow. We can expect a lot of change in the testing approaches and techniques which makes it essential that testers make an effort to stay updated on the trends that will define software testing in the years to come.