What if you discovered oil in your backyard? How would you get it extracted from your property and deliver it to customers? Where would you sell it and what would you charge? If the world’s most valuable resource is no longer oil, but data, how does your enterprise leverage the data it already creates and manages to turn what is ‘in your backyard’ into a sustainable revenue stream?
Still think wide-scale robotics is the stuff of science fiction? Think again: global spending on robotics and drones solutions will total $103.1 billion in 2018 alone, a 22.1% increase over 2017. By 2021, IDC predicts that spending will double, accounting for a compound annual growth rate (CAGR) of 25.4%.
Organizations are already using 3rd Platform technologies, including mobile capabilities, to enhance how they operate and interact with stakeholders. Knowing how to elevate and accelerate current initiatives is critical to executing a successful, Digital-Transformation (DX) based strategy. One way to use these tools to accomplish a DX-driven goal is to combine these technologies to maximize value for their organization.
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.
