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FORUM
OVERVIEW

Trinidad and Tobago is well placed to be the regional Big Data leader.

 

By bringing together key stakeholders, the Forum explores the transformational potential of Big Data and look at ways to build and promote trust, collaboration and innovation across multiple sectors.

 

The Forum illustrates the potential for Big Data to add value and reduce risk across business, social and economic spheres.

 

The Big Data Forum is a two-day event with a mix of panel discussions, keynotes and case study presentations where influential actors gather to shape the future of Big Data in Trinidad and Tobago, and regionally.

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TARGET
AUDIENCE

Government actors with responsibility for shaping the environment that facilitates Big Data usage;

 

CEOs, Small and Micro Enterprise (SME) business owners and private sector leaders mandated with redefining ‘digital’ business models, more efficient supply chains, and new sources of revenue;

 

IT developers & designers with technical expertise to establish data engineering skills into business processes;

 

IFI’s contributing resources for digital transformation and innovation;

 

Data Analysts and Scientists with responsibility for applying technological infrastructure to improve quality and value of data as part of the digital economy;

 

Academicians contributing to Big Data research material across various databases and repositories.

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KEY
AREAS

The Forum is proposed along the following key thematic areas:

 

1. Data Science and the future smart society;

 

2. The transformational role of Big Data Technologies and Analytics; and

 

3. Big Data, Artificial Intelligence and a smarter future

 
 
 

THE PHILOSOPHY

Good data used well can help us make better decisions. The availability of Big Data and the capacity to analyze it are vital for more effective decision-making at a global, regional and local level.

 

The Big Data Forum promotes discussion, forge partnerships, generate strategies and encourage research to harness the power of Big Data for sustainable development and economic growth.

 

The conference brings together international experts, representatives of government, local and global businesses,  academia, civil society, and youth.

 

Through a mix of panel discussions, keynotes and presentations, participants are exposed to the latest Big Data methods, tools and ideas, best practices in building trust, and others in the field with whom they can collaborate.

THE OBJECTIVES

1. To bring together all stakeholders in the data value chain to exchange ideas, experiences and practices, and present case studies and research on the effective use of Big Data to create public value.

 

2. To explore the opportunities of Big Data analytics and examine how new and innovative data sources, and information generated outside the official statistical system, can be incorporated into mainstream statistics.

 

3. To strengthen data partnerships and collaboratives among stakeholders, including youth, to expand Big Data research and usage.

 

4. To expand Big Data projects and citizen generated data by mobilizing private investment.

THE 2021 THEME

Exploring the Science of Big Data: A smarter future for Trinidad and Tobago

Data, technologies, and people are the three pillars of data science. The second edition of the Forum is designed to explore these core pillars in the era of Big Data; to examine the key components of each, to identify systematic and well-defined approaches to extracting value from Big Data and Artificial Intelligence, and to assess the readiness of Trinidad and Tobago and the wider Caribbean to transform Big Data into information and knowledge.

 

Thematic Areas

 

1. Data Science and the Future Smart Society

  

Big Data analytics and challenges require persons who can critically think about big data problems and who possess the necessary skills and knowledge to solve big data problems using big data technologies. The Forum examines the role of academia and education in big data and data science, equipping the region with the appropriate skills and competencies to address big data challenges correctly and reliably; assessing the local and regional demand for data science, the technical components of data science education and data science as a tool. It explores the tech startup ecosystem, AI workloads and the role of data science professionals in the smarter future.

 

2. The Transformational Role of Big Data Technologies and Analytics

Data Science embraces Big Data infrastructures including big data warehouses, in-memory computing, as well as big data enabling technologies such as platforms of intelligence. 


Rapid advances in computing technologies, software technologies, and parallel processing frameworks including the increasing popularity of web-based software continue to define the big data era. Accordingly, the Forum discusses open-source frameworks, storage and big data processing, the role of technology and analytics in the era of digital transformation, how Big Data technologies, applications and services can be tools to develop economic sectors and explores how platforms of intelligence can support the development of a Big Data Centre of Excellence.

 

3. Big Data, Artificial Intelligence and a Smarter Future

  

A data-driven future smarter society must embrace different data sets that can complement traditional forms of data. In the Big Data era unstructured and semi-structured data such as social media data and web data and other similar type data sets can have the potential to improve sustainable development, increase service delivery to the most vulnerable, advance interoperable modern data ecosystems and address everyday challenges through better data analytics and trend analysis.


The Forum completes the pillar of Data Science by examining Big Data, Artificial Intelligence and machine learning as powerful analytics, real world practical applications of AI, how applying more intelligent and advanced forms of analytics can extract more value from Big Data, Big Data management and machine learning, and Agenda 2030 and how data-driven algorithms and statistical models can help analyse data sets that produces real time inferences.

 
 
 
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