5 big data software solution trends in Intellectual Property management

 

Big data has the potential to improve the quality of business decisions by enabling text and data mining of vast amounts of data and delivering actionable insights which in the domain of Intellectual Property management is invaluable. Big data software solutions has created waves in the technology circles with discussions around it’s applications to commerce, retail, consumer data, finance and other areas. However another segment less mentioned where big data solutions are highly relevant is the intellectual property and patent data management domain.

Current trends make it very clear every organization has to have a strong big data strategy to ensure that the business maximizes their insight into big data sources (patent documents in this case). Big data is now a broad level business critical area and if approached correctly, can deliver improved results from better decisions based on smarter insights.

Here are 5 big data software solution trends that are currently leading in domain of Intellectual Property management.

1)      Creating IP Dashboards:

 There will be a rising interest in mining big data in the form of patent documents and intellectual property , extract and present some highly customized, business specific insights delivered in the form of an executive dashboard to gain competitive edge.

Developing a highly customized IP dashboard can help extract business critical insights from big data across multiple IP data sources and display insights that are tailored to the department, function or decision maker the data is aiding. With each organization or IP analysis department having its own specific workflows and requirements from IP related big data, the development of custom dashboarding applications will be an ongoing area of interest for the next year and beyond.

 

2)      Business Decision Modelling:

Big data provides an opportunity for an organization to develop software systems which take bulk raw data, process and analyse it to deliver information and insights that have a can have tangible impact on business processes and decisions. With a lot of information technology putting emphasis on big data solutions, within the intellectual property data management domain, there will be a continued focus on developing better business decision modelling systems that first identify what are the insights required to make smarter decisions within the organization and then working backwards towards building software which can mine data and deliver those.

Developing improved business decision modelling systems that are built on top of IP related big data will continue to grow as a focus area.

3)      Custom Analytics Insights:

 Data mining and custom analytics gives organizations a clear insight into the recent movements that are trending in their field of research. IP data can be used across various functions of an organization from R&D, engineering, product development, marketing and even finance. Each function requires different outcomes from the processing of patent data and as a result, custom analytics solutions that offer relevant insights and reporting will be another focus area within IP big data solutions development. For example, a company planning to invest in the renewable energy resources sector would need analytics and insights that track real-time developments across patent filings within wind energy, solar energy and tidal energy sectors. This could aid in spotting trends and innovation activity within each of the subdomains and understanding the movement within investments in renewable energy. Similarly, the analytics and insights another department within the same organization would be interested in accessing from big data would differ. The need for custom analytics software solutions within intellectual property big data will continue to see a rise.

4)      Advanced visualization for data mining:

 Advanced visualization of big data analytics gives a very clear and concise representation of insights in an ‘easier to interpret’ form. Like a number of other applications within big data, intellectual property data is complex, involves relationships between documents and patents, multiple sources, languages, geographies from which data is originated and could seem irrelevant when seen as a standalone document or in its text form. Advanced visualization techniques coupled with data mining has help present big data related to IP in a different light and creates perspective to the data. Heat maps, landscapes, relational charts, timelines, trend visuals and other forms of visualization has literally changed the way big data and the valuable insights it often hides are now seen and leveraged by organizations.

5)      Predictive analytics:

 Big data analysis does not always hold much gravity unless it can impact business decisions by projecting futuristic insights. Big data analysis solutions within intellectual property can project the future movement of trends on the basis of current and past trends. Development of predictive analysis software using IP big data is likely to see more demand. Continuing with the previous example, if a firm is planning to invest in renewable energy sources has historic analytics of patent data showing the trend map for solar, wind, thermal and tidal, then predictive analysis can help extrapolate those trends to ascertain future movement of activity in these areas

As the activity around developing software solutions for big data grows, intellectual property data management and analysis as a domain is also likely to see a lot of traction and these are just some of the trends that will pave the way for better and smarter information systems in this space.

 

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