Carnival Corporation, one of the world’s largest leisure travel companies,embarked on a journey to transform the experience of millions of vacationers through intelligent personalization.
At the core of this harmonious guest experience lies artificial intelligence (AI), powered by lots of data and the right foundational technological platform. This real-time digital traveler experience required trust worthy data to also travel seamlessly and be shared across an Internet of Things (IoT) network of intelligent sensors, digital portals and experiential wearable devices, and a data-savvy workforce that can apply actionable insights for customer satisfaction.
AI seems inevitably on its way to becoming ubiquitous. Organizations are using it to change the fabric of what they do and how they do it. But in scaling AI, data plays a crucial role. In fact,data determines if AI efforts will succeed. This has driven enterprises to derive significant business value from data, develop a data-first mindset and recognize data as a multi-dimensional phenomenon–Dynamic, Dependable, Distributed and Democratized, or “Data in 4D.”
A combination of skills, technologies and approaches has sparked this drive into the world of Data in 4D. Enterprises are now exploring ways to actualize value by building a business model that feeds on discoverable, visible, usable and connected data.With Data in 4D, companies can see all kinds of data–structured, semi-structured and unstructured–and implement ways to unearth valuable insights. It requires adopting a variety of approaches, technologies, systems and cultures to bring data into the realm of business decision-making.
But AI’s success is not just dependent on data. Areal implication of AI is on data itself. Many enterprises now recognize the importance of investing in a data-driven future. A recent study by Accenture and Everest Group of 200 global firms found that 72 percent forecast double-digit growth in data and analytics spend.To pay off, these investments must overlap the following four dimensions (4D) of data:
- Dynamic data is information derived from creating a boundaryless data value chain.The IT stack comprising the database, applications and infrastructure are no longer independent entities. Systems are breaking down boundaries between data, infrastructure and applications, and between humans and machines.Dynamic data helps enterprises accelerate their speed-to-insight, continuously retune supply chains and enable responsive, intuitive customer interactions. Dynamic or boundaryless systems, which utilize the cloud, have a uniform approach to data, security and governance.
- Dependable data is crucial to building trust, a critical component in an enterprise data strategy. As data can be both an asset or a liability, enterprises need an approach that prioritizes objectivity to foster trust as much as growth and profitability. This requires enterprise data to be dependable in quality, provenance and security. Organizations also need to ensure data quality and take proactive security measures. In addition,they must use advanced solutions such as AI to detect biased algorithms and eliminate unverified data from the decision-making process.
- Distributed data means information is no longer confined within the boundaries of an enterprise. Data sharing with peers, vendors and competitors is key to data monetization—increased efficiency, higher revenue and reduced cost. Organizations must securely share data across their internal and external ecosystems. This data sharing also enables the rapid development of innovative offerings and business models.
- Democratized data is about making business users data literate. To bea data-powered enterprise, business users must be able to access and explore datasets, identify new opportunities and generate relevant, trustworthy insights. This gives rise to a new paradigm where people haveaccess to the necessary skills and technologies to read, comprehend and use data.
Organizationsembarking on a data-driven transformation journey with Data in 4D must start with:
- The CEO taking ownership of the enterprise data strategy and appointing aC-suite executive to build and implement it.
- Investment in building the “Enterprise Data Platform” that powers data supply chains to be agile, well governedand operate at the speed of business.
- Fostering a culture of Data Literacy where business users can explore data, identify new opportunities and generate relevant business insights.
The raison d’etreof enterprise data architecture is to drive an organization to succeed on all four dimensions of data. Optimized by real-time data capture and analysis,Data in 4D lights the way to new, disruptive business models and innovative offerings, revealing new customer segments, markets and opportunities to boost productivity.