Training on Big Data for Official Statistics Training Course
Gain the skills you need to advance your career. This course offers hands-on learning, expert guidance, and real-world applications designed to help you grow.
Course Overview
| Course Title | Training on Big Data for Official Statistics Training Course |
| Organization | Tech For Development (T4D) |
| Venue | Tech For Development (T4D) Training Center along Tala Road, Runda, Nairobi |
| Target Industries |
|
| Target Job Roles |
|
| Course Fees (Face-to-Face) | USD 1,100/KES 75,000 (Exclusive of VAT) |
| Course Fees (Virtual) | TBA |
| Training Modes | Virtual and face-to-face training |
| Payment | Payment should be made to the Tech For Development (T4D) bank account on or before the start of the course |
| Accreditation | Tech For Development Certificate of Course Completion |
Course Overview
This intensive course offered by T4D is designed to equip participants with the knowledge and skills needed to effectively harness big data for official statistical purposes. Over the span of 5 days, this comprehensive training will delve into various big data sources, analytical techniques, and the integration of advanced tools like Hadoop to enhance the quality and scope of official statistics. Participants will gain hands-on experience with real-world datasets and learn how to address common challenges in data acquisition, processing, and analysis.
Duration
5 days
Personal Impact
- Develop expertise in handling and analyzing large datasets.
- Gain proficiency in using advanced tools such as Hadoop for big data processing.
- Enhance your data-driven decision-making skills.
- Expand your ability to generate insightful statistical reports.
- Improve your career prospects in data science and statistical analysis.
Organizational Impact
- Foster a culture of data-driven decision-making within the organization.
- Improve the quality and accuracy of official statistical reports.
- Enhance the organization's capacity to manage and analyze big data.
- Stay ahead of the curve by integrating innovative data processing techniques.
- Strengthen compliance with legal and ethical standards in data management.
Course Objectives
- Understand the significance and applications of big data in official statistics.
- Learn to identify, acquire, and process various big data sources.
- Develop skills in data visualization and insights discovery.
- Apply machine learning techniques to analyze big data.
- Utilize Hadoop for efficient data storage and processing.
- Address common methodological, privacy, and IT challenges in big data.
- Explore the use of mobile, GPS, geo-spatial, and social media data in statistical analysis.
- Develop strategies for big data integration in developing countries.
- Enhance collaboration and partnership strategies for big data projects.
- Implement innovative solutions for big data challenges in official statistics.
Course Modules
Course Outline
Module 1: Introduction to Big Data in Statistics
- Big data and the international statistical community
- Commonalities on benefits and challenges of big data sources
- Common methodological issues and quality concerns
- Common privacy issues: Legal frameworks, ethical guidelines, and trusted technology solutions to safeguard privacy
- Common issues on partnerships: Data acquisition and division of responsibilities
- Hadoop Integration: Using Hadoop for distributed storage and processing of large statistical datasets
Module 2: Mobile and GPS Data in Statistics
- Mobile phones, GPS, and other tracking devices
- Typology of data sources
- Challenges in using mobile and GPS data
- Partnerships for data acquisition and analysis
- Mobile phone devices and ICT indicators
- Hadoop Integration: Leveraging Hadoop's HDFS to store and analyze large volumes of mobile and GPS data for ICT indicators
Module 3: Geo-Spatial Data and Remote Sensing
- Satellite imagery and other geo-spatial information
- Typology of geo-spatial data sources
- Challenges and partnerships in geo-spatial data
- Use of satellite images for measuring agricultural crop production
- Combining social, economic, and environmental statistics utilizing geo-spatial data
- Hadoop Integration: Utilizing Hadoop's MapReduce for processing satellite imagery and integrating geo-spatial data for comprehensive statistical analysis
Module 4: Social Media Data and Web Scraping
- Twitter and other social media
- Typology of social media data sources
- Challenges and partnerships in social media data
- Use of social media data for official statistics
- Web scraping for labor statistics and online price data capture
- Hadoop Integration: Employing Hadoop for storing and processing vast amounts of scraped data from social media and web sources to generate official statistics
Module 5: Big Data Strategy and Development
- Big Data and development
- Big Data strategy
- Big Data in developing country circumstances
- Introducing innovation in statistical practices
- Common IT issues: Cloud computing and data processing solutions
- Hadoop Integration: Developing strategies for implementing Hadoop in big data projects, especially in developing countries, to enhance data processing capabilities and innovation in statistical analysis.
Course Administration
Methodology
This instructor-led training course is delivered using a blended learning approach comprising presentations, guided practical sessions, web-based tutorials, and group work.
Accreditation
Participants will receive a Tech For Development Certificate of Course Completion.
Training Venue
Held at the Tech For Development Training Centre.
Accommodation & Airport Transfer
Arranged upon request.
Email: letstalk@techfordevelopment.com
Phone: (+254) 790 824 179
Tailor-Made
Customised training available.
Payment
Send proof of payment to letstalk@techfordevelopment.com.
