Blue BI participated with Nicola Celli and Andrea Astolfi at the Gartner Data & Analytics Summit held in London from 22 to 24 May 2023.
The theme of the conference was “Lead for Purpose, Make an Impact”: companies must conduct their work with a clear purpose in order to create an impact.
The Summit was a chance to understand what are the most significant challenges that Data Analytics companies are dealing with and understand how to implement strategies and innovations supported by data and analytics to guide companies in a targeted way balancing confidence, responsibility, governance and security with adaptability and responsiveness.
Organizations are increasingly harnessing the power of data and analytics strategies to optimize decision making. For this, leaders in the world of Data Analytics must be proactive in driving the organizational and cultural transformation needed to become a data-driven enterprise and implementing targeted strategies that maximize the company’s capabilities.
ChatGPT and Generative AI were the protagonists of the event: the disruption that these tools are bringing into our lives and our work is evident and involves a radical re-evaluation of future prospects.
The topics of the Summit
Here are some of the topics addressed during the Summit:
The advent of Generative AI
Generative AI, one of the emerging applications in the field of Artificial Intelligence and disruptive in recent times, is revolutionizing the way content is created. We are witnessing experiments in every field: marketing, design, e-commerce and medicine are just a few examples.
The role of the future: Prompt Engineer
Generative AI also has consequences for the roles that will be sought in the future in the labour market. We are talking in particular about the Prompt Engineer, the person who working on natural language processing projects (NLP) establishes prompts, rules and precise indications to produce desiderable and useful results.
Data management
Data is the most important resource of an organization and is essential for the analysis and application of Artificial Intelligence (AI) and Machine Learning (ML). The Summit discussed current and future strategies for data management.
An increasingly important C-level in organizations: CDAO
Chief data and analytics officer (CDAO), leadership and corporate responsibility to create value through the ecosystem of corporate and non-business data. Let’s talk about Data observability, Data lineage, Data Catalog, Data quality, etc… Some paradigms certainly known and important for some time, others new and/ or revalued, certainly important for the data-driven evolution of organizations and whose management today has a clear manager, the CDAO.
Analytics and Innovation
D&A leaders need to shift their focus beyond the implementation of analytics capabilities toward achieving business outcomes to increase the impact of analytics on organizations. During the Summit, we discussed the innovative technologies of Data Analytics and the best practices in their use to drive innovation.
Strategy and Value
Data and analytics are part of every business discussion about digital transformation. This requires creating a D&A strategy that can impact organization priorities, establish and manage value expectations, and build an operational model to execute. The Summit discussed how to identify, assign value and prioritize investment in data and analytics, as well as how to develop a coordinated strategy and operational model to ensure success.
Data Science, Machine Learning and Intelligenza Artificiale
Data, Machine Learning and Artificial Intelligence are the key to create value and influence how decisions are made within the organization. The conference discussed new technological trends, organisational requirements and the development of skills and talent needed for successful implementation.
Trust, governance and privacy
To take advantage of business opportunities and challenges, organizations must establish the right foundation for data and analytics governance. Trust, privacy, ethics and responsibility are fundamental. In this area of security and transparency of AI algorithms, an increasingly important role is that of Explainable AI, the set of AI technologies that offer an explanation for their predictions and that therefore can be intuitively understood by humans.
