Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
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A data integration strategy and information management within a sizeable organization can be incredibly difficult to define and even more difficult to implement. Organizations need a way to manage data while making the best use of available and appropriate technology platforms to process all of the different types of data within an organization.
The current trend indicates that most organizations tend to rely on (or are planning to rely on) in-house CX development, while just under 30% of organizations surveyed said that they were using or planning to use outside specialists to assist them with implementing their CX strategies and programs. I see this trend changing over the next 12-16 months, with the use of outside CX consultancies increasing in order to satisfy current and future demands for CX adoption.
In this Advisor, we examine five measures to demonstrate success in continuous integration and testing efforts.
In this Advisor, we examine autonomous systems. These systems are on track to find widespread adoption. They will be a game changer and will propel new research, development, and business opportunities. It’s no wonder they are attracting the interest of researchers, manufacturers, and users alike.
We feature five articles in this CBTJ, covering a wide range of issues relating to the digital shift — from securing executive-level buy-in during the transition and overcoming organizational/cultural inertia to creating a holistic overview of the enterprise and mapping the digital value-creation process.
To bridge the divide between the general understanding of the concepts that drive the business model and the departments and teams into which the employees have been divided, the organization has to make the leap from a model-driven data architecture to a model-driven organization; it has to derive its own structure from the logical design.
According to Cutter Consortium Senior Consultant Mike Rosen, there are three main roadblocks to digital business: 1) Lack of an agile architectural approach; 2) Limited data accessibility, integration, and quality; and 3) Inability to accommodate new requirements for speed, scope, and scale. Discover practical strategies for approaching and tackling these roadblocks in this short, on-demand session.
The early emergence of a new, potentially viral term — a “lakehouse” — suggests another wave of fuzzy thinking is about to infect the data architecture space.