Big Data: New Opportunities in Economic and Statistical Analysis

Why Attend

Encompassing the dramatic rise of computational technology, big data empowers researchers to explore and understand complex statistical as well as economic challenges. In 2020 covid-19 created a global crisis and now more than ever, it is time to make the most of the opportunities Big Data derives. Big data is already transforming the financial industry: market players actively use data patterns from micro datasets to produce new and timely indicators. But, has Covid-19 created new opportunities and risks that central banks need to consider? For central banks and regulators, big data opens up unprecedented possibilities. These include: enhancing financial stability assessments, applying new approaches to economic forecasting, as well as obtaining rapid feedback on their policies. Yet, in order to make the most of these new opportunities, the central banking and supervisory community still needs to overcome a number of methodological, technical and institutional challenges. This course, “Big Data: New Opportunities in Economic and Statistical Analysis”, will look at key topics from best processes for data management and analytics, the opportunities the cloud brings for data management to what good governance looks like when managing big data. Each day will feature three hours of expert-led live content to maximize the opportunity to share and learn. The Course chair will ensure participants have opportunities to network throughout the programme.

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Course Objectives


  • By the end of the training course, participants will be able to:
  • • Effectively manage large amounts of data
  • • Understand the opportunities that cloud and data management have and the relationship between cyber resilience and cloud
  • • Design a supervision and surveillance analytics framework
  • • Use new tools and techniques for visualising new data sets
  • • Understand the importance of good governance of big data and create an effective governance framework for balancing oversight and encouraging innovation


Target Audience


Central Bankers only

Foundations and building blocks of Big Data

 

Big Data 2021 - Course introduction and participant welcome

  • Introductions and welcome from the chair
  • Overview of the training course and key themes
  • Discussion of delegate expectations and particular areas of interest
     

Overview of new data sources in economics and finance

  • Big data and central banking – Purpose and use
  • Fintech, data never sleeps
  • Quality and transparency of new data sources

 

Big data and central banks

  • Opportunities
  • Organising big data work
  • Challenges
  • Policy issues with handling and using big data

 

Machine Learning and Statistics: Variations on a Theme

  • Machine learning and statistics
  • Classifying data-analysis methodologies
  • What are the limits of our predictive capacity?
  • Pitfalls and hidden strengths of machine-learning methods

 


New challenges for Big Data and data management

 

Making sense of Big Data through Artificial Intelligence (inc. text mining)

  • Big data - general introduction
  • Big data information for central banks
  • Working with big data at central banks: Artificial Intelligence potential & main applications
  • Machine Learning
  • Network Analysis
  • Text mining

 

Applying data science in economics and finance

  • Data science models for large datasets
  • Using predictive models in macroeconomics
  • Case study: Working with big data, models, software and examples from Bank of Italy

 

Visualisation: new tools and techniques for data storytelling

  • Why is good data visualisation and storytelling important?
  • Overview of best practise techniques
  • How the Bank of England is using state of the art technology
  • Examples of improved communication of financial data using these techniques and technology
  • Discussion: where are the opportunities for central bank communication?

Effective use of Big Data

 

The building blocks of Big Data

  • New applications of open source technologies in data collection, management and analysis
  • Overview of key models and analytics frameworks
  • Tips for management of sensitive issues in the areas of security standards and confidentiality
  • Effectively managing large amounts of data

 

AI and ML implications for data management and analytics

  • Current capabilities of AI and machine learning
  • Data management, processing and analysis
  • Examples of machine learning based software solutions for the regulators and the regulated
  • Discussion: what are the best opportunities in AML and CFT

 

Good governance: how should central banks manage Big Data

  • Key approaches and challenges to successful governance of Big Data
  • Framework for effective management of Big Data
  • Strategies to balance oversight and promote innovation
  • Discussion: How effective is existing data governance in coping with Big Data?

 


Advanced uses of Big Data

 

Advanced Statistical Analysis of Large-Scale Web-Based Data

  • Data science methods for big data
  • Case study using social media data 
  • Challenges and learnings

 

Cloud and data management: innovation and opportunities for central banks

  • Examples of cloud applications in today's central banking environment, advantages and disadvantages 
  • Importance of cloud computing for data science and big data analytics 
  • Discussion: what does it take to effectively manage limitations and potential legal and security risks?
     

Closing remarks and delegate action plans

  • Summary of the course
  • Discussion of the observed trends and case studies 
  • Application of learning points in the delegates’ home organisations
  • Preparation of action points

Implementation Workshop

Benefits of attending the Implementation Workshop: 

  • Developments in the area since the live content sessions, including new resource material
  • Questions arising since returning to the central bank
  • Challenges of implementation: where are the roadblocks?
  • Medium-term goals: what is realistic?

Establishment of group network to keep in touch with peers and share best practices

Step 1: Select Prefered Schedule


Date Fee (GHS)

Step 2: Choose Registration Type