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ACADEMIC

STUDENT DEVELOPMENT. 86% Graduate Employability 2018 26,418 Graduates since 2005 Professional Certification – Microsoft Data Science, CISCO, Oracle, Lean Six Sigma, etc. ACADEMIC. 8 Faculties 86 Programs (PhD, Master, Bachelor, Diploma) 10,930 Students Enrolled

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ACADEMIC

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  1. STUDENT DEVELOPMENT • 86% Graduate Employability 2018 • 26,418Graduates since 2005 • Professional Certification – Microsoft Data Science, CISCO, Oracle, Lean Six Sigma, etc. ACADEMIC • 8Faculties • 86Programs (PhD, Master, Bachelor, Diploma) • 10,930Students Enrolled • 677International Students UTeM MELAKA INDUSTRIAL ENGAGEMENT T.U.N.A.I • More than 100industry partners • Industrial Labs – Samsung IoT, ST IoT Academy, CISCO Academy, Microsoft IT Academy, Oracle Academy • Active alumni and community programs CONCEPT TECHNOLOGY A University that produces highly skilled technologists and enhances inventions, impacting industries and society RESEARCH @UNIVERSITY ADVANCING • Niche Area : Advanced Manufacturing & Computing Technology • 6Centers of Excellence INDUSTRIES HUMAN RESOURCE • 2,065staff (880 academicians, 1,185 administrative) • 326 Professional Certified staff – Technologist, Ir., C.Eng, Gs., L.Ar ., etc • 55.1% staff with PhD • Academics appointed as experts and consultants – OIC Cert, Blockchain Technology, CTFL Cert, etc.

  2. Leveraging AI and Data Analytics For SME Success By SharifahSakinah Syed Ahmad, Phd Department of Intelligent Computing & Analytics (ICA) UniversitiTeknikal Malaysia Melaka (UTeM)

  3. How much data generated every minutes? https://www.visualcapitalist.com/big-data-keeps-getting-bigger/

  4. Big Data Statistics 2019 https://techjury.net/stats-about/big-data-statistics/

  5. Digital Indonesia 2019

  6. How AI & Data Analytics help SMEs As social, mobile and cloud technologies become more prevalent, these words are thrown around a lot, but are these processes valuable only for big businesses or can small and medium-sized enterprises (SMEs) benefit as well?

  7. Data analytics for SME

  8. Designing and Deploying Analytics https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/unlocking-the-power-of-data-in-sales

  9. Analysing data Data gathering Obtaining insights from data

  10. Five Data Analytics Applications for SMEs

  11. Five Data Analytics Applications for SMEs Today, we have access to more data than ever before. Due to this overwhelming multitude of data, it is extremely difficult for SMEs to make any sense of these data.  Therefore, SMEs may choose to leverage on Business Intelligence (BI) tools like Tableau and Power BI to build dashboards to monitor business indicators at a glance.

  12. Five Data Analytics Applications for SMEs Stocking the shelves with the right product mix will also enhance SMEs’ revenues while avoiding costs associated with over-stocking.

  13. Five Data Analytics Applications for SMEs • All businesses seek to get the right information to your target audience’s eye level when customers are evaluating the purchase of similar products or services. But how is this done in practice? • Clusters (Customer segmentation) • Propensity models (Predictions customer behavior) • Collaborative filtering (Recommendations) 

  14. Five Data Analytics Applications for SMEs Another common business objective is to enhance the average spend per customer through cross-selling. In practice, SMEs’ frontline staff are likely to possess different levels of expertise in this art as their experience levels and observation skills vary. To provide for better training and guidance to staff members, restaurateurs need to get a solid understanding of groups of products customers typically buy. 
 Market basket analysis

  15. Market Basket Analysis

  16. Five Data Analytics Applications for SMEs • Enhanced digitalisation has provided a treasure trove of unfiltered customer sentiments on social media platforms that SMEs can tap on to adjust or enhance their products. • Increasing customer engagement • Personalize recommendation

  17. Challenges of SMEs in applying AI to Data Analytics • Many SME businesses do not know how to analyse data! • Data Quality • Usability & relevancy • Data Collection • Consistency • Continuous process

  18. SMEs in relation to data • Those who are ignorant about benefits of data, have not started to use their data • Those who know data is important but struggling with the right way to get results form their data/ or given using data due to bad experience Business Intelligent (Vs AI) • Those who know data is important and beneficial

  19. Data issues with SMEs • Did not capture due to ignorance about importance of data • Did not capture relevant data or sufficient data to benefit from AI • Unable to benefit from data from government sources to generate insights for their unique selling proposition. • Not willing to spend money on this area as they prefer to spend to running data to day operations with no improvement • Not aware or what to do and cannot afford to hire consultants for this area • Not willing to look at future as they are not sure if they can survive.

  20. Future Technology

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