Navigating the Era of Big Data: Challenges, Opportunities, and Trends

🎙️ An Interview with Prometeon and Avvale.

Modernity is characterized by the Era of Big Data, with an explosion of data generated, collected, and globally analyzed due to digital transformation. Although data analysis offers competitive advantages, it requires robust infrastructure and security management.

Following its separation from the Pirelli Group, Prometeon faced challenges in data management, necessitating a digital transformation journey to enhance operational efficiency and promote a data-driven culture. The ultimate goal: a comprehensive and flexible data platform. The Avvale team is supporting Prometeon in this Data Modernization journey, enabling them to immediately experience the benefits gained through this transformative process.

With Luigi Rizzo, Data Platform & AI Manager at Prometeon Tyre, and Mario De Stefano, Data Platform & AI Practice Director at Avvale, we wanted to delve deep into discovering the opportunities, challenges, and trends in the realm of Data, providing valuable insights to maximize the value of data assets broadly.

A Word from Luigi Rizzo (Data Platform & AI Manager – Prometeon)

🎙️ Who is Prometeon?

Prometeon Tyre Group is the only tyre manufacturer entirely focused on the Industrial sectors, namely transportation of goods and people, Agro, and OTR. The Group has 4 factories (two in Brazil, one in Egypt, and one in Turkey), 4 Research & Development centers (Italy, Brazil, Turkey, and Egypt), and a Development Center in Egypt. Approximately 8,000 people from over 40 nationalities work within the Group, present on all 5 continents.

🎙️ What are the main challenges that a company like Prometeon is facing in the era of data, and how are you addressing them?

The tyresector is continually evolving in the data era, with challenges and opportunities requiring efficient information management. The main challenges we face are:

• Integrating Operational Technology (OT) with Information Technology (IT) to leverage data generated by sensors and machines in our plants, transforming them into insights to improve quality, safety, efficiency, and sustainability. 
• Maximizing the use of internal and external data to make evidence-based decisions, promoting collaboration across functions and a data-oriented culture. 
• Modernizing the technological landscape by adopting modern cloud solutions, Generative AI and Machine Learning to strengthen data management and analysis capabilities, adapting to current and future needs.

🎙️ What are the emerging trends in your sector driving the need for better data and information management?

Some trends in our sector are driving the need for better data management, including:

• Increasing demand for intelligent and connected tyres, requiring integrated chips to collect and transmit data regarding vehicle conditions, road conditions, and energy efficiency.
• Precise requirements from regulatory bodies mandating legal tests on tyres, requiring reliable data on performance and regulatory compliance. 
• In-depth analysis of global markets influenced by socio-political events, requiring a comprehensive and up-to-date view of needs and opportunities based on internal and external data.

These trends compel us to invest in data management to provide competitive and sustainable solutions. To do so, we must address various technical and strategic challenges, which we will seek to outline in the following questions.

🎙️ What are the main objectives when undertaking a data project, both technical and strategic? What are the complexities?

Among the objectives that need to be set are:

• Technical objectives: creating an integrated and scalable platform to manage data, ensuring quality, security, and compliance, developing analytical and predictive models, leveraging emerging technologies such as AI, cloud, and IoT. 
• Strategic objectives: defining a digital vision, aligning business goals with data capabilities, engaging and training staff, and creating a data-driven culture. 

The complexities faced are related to data fragmentation and heterogeneity, integration between systems and countries, data privacy and protection, resistance to change, and skills shortage.

🎙️ How important is it to transition from a process-driven organization to a data-driven one, and how do you involve employees in this digital transformation?

The transition from a process-driven reality to a data-driven one is essential for competitiveness and innovation. Data is the new lifeblood of organizations, which must be able to collect, analyze, interpret, and leverage it to create value and improve performance.

We actively involve all departments in all project phases, defining new data models, and providing an extensive training program for approximately 3000 employees on data analysis and visualization tools.

A Word from Mario De Stefano (Data Platform & AI Practice Director – Avvale)

🎙️ How has the data and technology landscape changed over the past few years, and how does Avvale respond to these changes?

In recent years, the data landscape has changed significantly due to three factors: the increase in available data, advances in AI, and growing concerns about security and privacy. Customers' business models are also progressively evolving towards more circular and sustainable models. Avvale, thanks to the vision of its founder Domenico Restuccia, has anticipated this trend, promoting a vision in which technology is a powerful multiplier capable of creating a sustainable and profitable future.

To adapt to these changes, we focus on various initiatives, including:

• Continuous training on advanced technologies and methodologies. 
• Collaboration with Technology Partners to ensure best practices. 
• Compliance with data privacy and security regulations through rigorous governance. 
• Use of agile methodologies to adapt quickly to technological changes and customer needs.

🎙️ What are the most common challenges in the data field, and how do we contribute to addressing them?

Companies seeking to improve their Data Management and Data Analytics capabilities often encounter a series of quite common challenges. Here are the main ones and our strategies to overcome them:

• Inadequate data quality
  PROBLEM: Dirty or incomplete data leads to unreliable results and wrong decisions.
  SOLUTION: Data cleansing solutions and a Data Governance framework improve data quality.
  
  
• Data silos 
  PROBLEM: Data isolated in departments generates redundancy.
  SOLUTION: Promote data integration with Data Management platforms.
  
  
• Scalability of analytics solutions 
  PROBLEM: Analytics solutions do not keep pace with data growth.
  SOLUTION: Serverless architectures and cloud computing dynamically manage workload.
  
  
• Data security and privacy
  PROBLEM: Protecting sensitive data and ensuring regulatory compliance.
  SOLUTION: Implement security policies and support understanding of privacy laws.
  
  
• Costs and ROI
  PROBLEM: Justifying investment in Data Analytics solutions.
  SOLUTION: Measure KPIs demonstrating the value of data management.
  
  
• Cultural change
  PROBLEM: Internal resistance to adopting a data-driven culture.
  SOLUTION: Conduct awareness sessions and promote data use in daily decisions.

🎙️ What does it actually mean to build a Data Platform? What are the benefits?

Building a Data Platform means creating a centralized environment to collect, store, manage, analyze, and distribute data within an organization. It facilitates data access, improving operational efficiency and supporting decisions based on reliable and timely data.

The benefits include:

• Data centralization: reduces data silos, enhancing collaboration and facilitating access.
• Informed decisions: enables quick decisions based on concrete information. 
• Automation: reduces manual workload and speeds up operations. 
• Scalability: facilitates adding new data sources and functionalities without disrupting business activities. 
• Innovation: supports new business models, products, and services. 
• Security and Compliance: improves control over security and regulatory compliance.

🎙️ What are the key pieces of advice that can be offered to clients to maximize the value of their data?

To maximize the value of data in an organization, it is critical to take a holistic and strategic approach. Below are some key tips we offer our clients:

• Define a strategy: align business objectives with data utilization, ensuring its quality, identifying the most important, and understanding how it can drive business value. 
• Adopt advanced Analytics techniques: to extract valuable insights, predict trends, and optimize operations.
• Data-driven culture: promoting the everyday use of data and encouraging experimentation and iteration.
• Data Governance and Integration: establish robust data governance to manage access, security, and compliance, integrating sources for a comprehensive view.
• Scalability, flexibility, and constant monitoring: build scalable, adaptable infrastructure and monitor data effectiveness with performance metrics.

By addressing these issues with a structured approach, organizations improve their operational efficiency and identify new opportunities for growth and innovation through the strategic use of data.

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