Data management is a major concern for enterprise organizations, and for good reason. IDC forecasts that by 2025, the global datasphere will grow to 163 zetabytes (ZB). Access to all this data will unlock unique user experiences and a new world of business opportunities for organizations. Data is becoming increasingly diverse, dynamic, and distributed across on-/off-premises, including public cloud. Hybrid cloud environments combine these platforms to increase the benefits of data collection and use, but they come with their own set of challenges. These hurdles prevent organizations from efficiently managing and deriving maximum value from all their data.
The Internet of Things (IoT) is rapidly revolutionizing how enterprise organizations work, and technology budgets are increasingly reflecting the need for IoT investment. At least $3.1 billion of IT consulting services and $11.2 billion of systems integration services will be consumed building and implementing IoT solutions worldwide in the next three years. Organizations recognize that today’s faster pace of business and their desire for digitally enhanced business transformation means a bigger technology budget.
Following the 2014 Summer Davos Forum, China’s State Council issued a series of formal opinions in 2015 that outlined detailed general principles and measurement guidelines meant to encourage entrepreneurship and innovation, pursue innovation-driven development, and improve employment in China.
IDC’s research shows that today’s systems of record are being replaced by new systems of intelligence, which layer in new autonomic and predictive intelligence assets. This revolution, fueled by Digital Transformation, is highly visible in the ERP application suite.
IDC calls this enhanced ERP portfolio “intelligent ERP” (i-ERP) and “intelligent applications” (i-Apps). These products are starting to run businesses in an increasingly digital world.
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:
While today’s business environment is already digitally-powered, new technology advances are poised to deliver a radically new system of commerce. In fact, IDC predicts that by 2020, 50% of the Global 2000 will see much of their business depend on their ability to create digitally-enhanced products, services, and experiences. This expansion of Digital Transformation (DX) at a global scale signals a new digital economy.
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.