There are two primary ways to buy or trade data in the Data as a Service (DaaS) market – direct sales from a data provider to end users, or via a data marketplace. While large, established information services businesses continue to make direct sales to their customers, many are also participating in data marketplaces. For smaller and emerging providers of DaaS, the rise in data marketplaces has made it simpler for them to package and sell their offerings, and for potential customers to find them. Marketplaces simplify the searching process, providing a variety of sources and types of data, along with a ready group of potential buyers.
Data governance is no longer optional for enterprise organizations. Aside from complying with new regulations, such as the General Data Protection Regulation (GDPR), organizations are finally realizing the value of data as an asset that needs to be protected, managed and maintained to increase asset value. But just because businesses understand the value of data governance, doesn’t mean that enterprises are confident in their abilities to execute on it.
While it is a newer technology, blockchain is already disrupting financial services, insurance, healthcare and supply chain solutions. Two main causes of this disruption are blockchain’s ability to enable disintermediation, and how it provides an immutable historical record of data. Blockchain technology itself solves many of the problems that data governance professionals, and data management technology vendors have been trying to solve for years: group consensus on the most recent version of the truth for a given entity, and full instance lineage (provenance) of the data.
While blockchain has been able to transform these solutions, forward-thinkers are asking: will blockchain have the same disruptive effect on data management? There are two main factors to consider when assessing blockchain’s potential to disrupt data integration, storage, and data integrity:
As the market for intelligent applications and the software platforms used to build them has emerged, nomenclature confusion has grown. What should we call these applications, and what should we call the platforms, libraries and software tools used to build them?
The terminology matters. Vendors need to differentiate their products from the business intelligence and predictive analytics software that has existed for decades. ‘Intelligent applications’ and ‘business intelligence’ software provide two very different sets of functionality. For technology buyers who need to justify new solutions to budget holders, the terminology matters too.