Course Overview
This intensive course offered by IRES 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 Level:
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 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.
Related Courses
Course Administration Details:
Methodology
These instructor-led training sessions are delivered using a blended learning approach and include presentations, guided practical exercises, web-based tutorials, and group work. Our facilitators are seasoned industry experts with years of experience as professionals and trainers in these fields. All facilitation and course materials are offered in English. Participants should be reasonably proficient in the language.
Accreditation
Upon successful completion of this training, participants will be issued an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).
Training Venue
The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch. All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.
Accommodation and Airport Transfer
Accommodation and Airport Transfer are arranged upon request. For reservations contact the Training Officer.
- Email: [email protected]
- Phone: +254715 077 817
Tailor-Made
This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location. For further inquiries, please contact us on:
- Email: [email protected]
- Phone: +254715 077 817
Payment
Payment should be transferred to the IRES account through a bank on or before the start of the course. Send proof of payment to [email protected]
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