Data Exchange and Marketplace, a New Business Model in Making

comments

By Sarab S. Mann, MBA.

The Internet of Things (IoT) refers to the network of numerous physical devices, also known as the Internet of objects, refers to the networked interconnection of everyday objects (20 billion by 2020, according to Gartner). Such devices will be an integral part of next-generation computing, additionally, these devices will produce astronomical data volume, catapulting us into the world of zettabytes and yottabytes. Data is a new Oil, which is a byproduct of doing operations and for others, same data can be a catalyst to capture newer insights, build AI models and drive innovation.

If you love your data, set it free

The renewed approach to data democratization will open multitudes of new business opportunities:

Data Explorers and Data Miners: It would not be easy to find valuable data from massive data reservoir acquired from diverse sources. The exploration requires tremendous effort and there will be an opportunity for players and service providers who can choose an area or segment(s) and build competency.

Data Cleaners and Data Curators: Data cleaning is an important aspect of data management & transformation, and cleaning phase is tightly integrated with other phases. However, in the new paradigm entrepreneurs can voluntarily clean and curate data sets and sell these to data merchants and brokers with unique requirements.

Data Aggregators: Data aggregators are thriving but data democratization will allow more opportunities for the entrepreneurs who like to focus on a certain segment(s). For example, an individual developer builds a data product by reaping freely available geology data that can be highly valuable to oil and gas companies.

Data Producers: In the near future billions of IoT devices will produce data that may not be critical or valuable to the producers but definitely be a source of revenue for them, which will be sold through highly sophisticated data exchanges.

Security Management: Access management will be one of the toughest challenges data purveyors need to address. It is not easy to deploy multi-layer access mechanism. There will be the requirement for security professionals and companies who monitor and manage the access or develop the tools. Lee Painter, CEO of a new generation of IAM provider Hypersocket Software elucidate on AI's potential for intelligent, real-time security to implement fine-grained access control in a recent article.

Tools Provider: Technology entrepreneurs are developing new types of search techniques to query these vast stores of diverse data; AI tools can automatically catalog, condition and author the data. Several companies have already envisioned the requirements and are aggressively pursuing the opportunity.

Data Merchants: Data brokers have been thriving but data democratization will extend the opportunity and instead of negative image data brokers will be considered valuable in the data-information value chain. Oracle's acquisition of data brokering agency Datalogix enabled Oracle to introduce DaaS, Data as a Service on Oracle cloud. Oracle's initiative is one of the earliest moves towards more sophisticated and lucrative business model. Many cloud computing companies still focus on IaaS, PaaS, and SaaS but new entrant DaaS business model seems promising and lucrative; data professionals should be free to use their imagination to find insights and develop industry-centric products or solve complex problems.

Data governance and managing IAM(Identity and Access Management) will be considerable challenges and most recent incidents such as Cambridge Analytics-Facebook debacle will definitely make the data sharing arduous and susceptible to suspicion & mistrust. However, data exchange platforms such as Ocean Protocol along with blockchain offers promise in safeguarding data security.

Bio: Sarab S. Mann, MBA, is transforming large & diverse data sets into
competitive advantages. CDCR; Babson College - Franklin W. Olin Graduate School of Business.

Original. Reposted with permission.

Related:

• The Cold Start Problem with AI
• So, How Many Machine Learning Models You Have NOT Built?
• More Data or Better Algorithms: The Sweet Spot