Big Data in Technical and Vocational Education (TVE) Big Data in TVE By NAMBOBI MUTWALIBI Department of Technical and Vocational Education (TVE), Islamic University of Technology, Gazipur-1704, Bangladesh

Big Data in Technical and Vocational Education (TVE)

What is big Data? We define big data as the increase in volume, variety, velocity, veracity and value of data sets that require new forms of processing to enable greater decision making and insight discovery of interesting patterns. .

Outline and objectives 1. Concept of big data. 2. V’s of big data. 3. The tools and importance of big data in TVE.

V’s of big data cont.. 1.Volume – the amount of data is too big. 2. Variety- Data exists in different formats. 3. Veracity –trustworthiness and dependability of the information produced after analysis.

V’s of big data cont.. 4. Velocity: Describes the rate at which incoming data requires to be processed. (its always high) 5.Value: Refers to the benefits accrued after using the analyzed data

How big is the data? Source: IDC’s Data Age 2025 study.

A big picture about the data? The Library of congress collects text allover the world. And is the largest library in the world with digital books.

Big data! So what? TVET Directorates in need of big data.

Table here TVET Directorates in need of big data. Research Directorates/Bodies/Departments Possibilities of big data Research Trending research, text research and archive retrieval Student ,community development and Support Sentiment Analysis, Student behavior (Mitigate issues and Student complaints before they go viral), reputation management. Planning and Institutional Support Analytics from financial audits, recommendation engines and forecasts Examinations and Assessments Performance Perditions Curriculum Development and Support Industrial requirement and trends through text analysis Quality control Be aware of damages, risky control and social impact of the social media. spoting anomalies Legal leverage emails and documents Procurement and logistics Mileage analysis and changes in stock Human resources Performance tracking, recruitments, conflict resolution through text analytics of emails Table here

Where is the data? 1.Library and institutional clinics 2.Email, documents, spreadsheets 3.Data on mobile devices. 4.Web data and multimedia in files 5.File transfer and server logs. 6.Sensor data. 7.Social media, Messages. 8. ERP data, user engagement. 9. LMS, eLearning platforms, MOOCs

Big data tools

Big data tools 1.Spark- leverages grid computing for large parallel processing also using cloud services( Amazon) 2.R and Excel- statistical analysis 3.Hadoop/Map reduce -allows big problems to cut into smaller 4.Tableau-visualization and business intelligence tools 5.RapidMiner -predictive analytics & text analytics 6. Mapd,GraphX and Mlib- graphing analytics.

conclusion In order for TVE stakeholders to cop up with the way society uses data, it has to shift; i) from business focused to personal targeting (skill development and innovation motives); ii) from structured to unstructured; iii) from reflecting yesterday’s data to here and now; All in all putting privacy measures at a peak.

A Big Thank you NAMBOBI MUTWALIBI www.nambobi.com For more information, Reach me out www.nambobi.com or email me at hello@nambobi.com NAMBOBI MUTWALIBI www.nambobi.com

References Daniel, B. K. (2017). Big Data in Higher Education: The Big Picture. Switzerland : Springer International Publishing . Goel, V. P. (2017). TECHNICAL AND VOCATIONAL EDUCATION AND TRAINING (TVET) SYSTEM\. Retrieved from unevoc: http://www.unevoc.unesco.org/up/India_Country_Paper.pdf IDC. (2017). Data Age 2025: The Evolution of Data to Life-Critical Don’t Focus on Big Data; Focus on the Data That’s Big. Morabito, V. (2015). Big Data and Education: Massive Digital Education Systems Big Data and Analytics (pp. 47-64): Springer.