The Analyst Team

Nur Syuhada Abdul Razak
Research Analyst
Syuhada is a Research Analyst in Omdia’s consulting team for Components and Devices, providing market research, analysis, forecasting, and insights to ProAV industries, mainly focusing on the Hospitality TVs market.
Previously, she was a part of Omdia’s research operations team, contributing to the research and analysis support for various research products across pillars. Before joining Omdia, Syuhada worked as a Market Analytics and Organizational Strategy at Malaysia’s Agricultural Bank. She was in charge of market research, trend analysis, forecasting, and formulating strategic direction and plans for the bank. Syuhada holds a bachelor’s degree in actuarial science from Drake University, US, and a master’s degree in finance from International Islamic University Malaysia.

Joanne Goh
Research Manager, Manufacturing Technology
Joanne is a research manager in Omdia’s manufacturing technology team, covering the Electric Motor System and Discrete, Process, and Capital Equipment research portfolios. She previously worked as the lead analyst for Omdia’s low-voltage motor drives intelligence service. Joanne has also done extensive research on motor-driven equipment and the motors and drives market across all vertical applications.
Joanne joined Omdia (formerly IHS Markit) in 2015. Previously, she was an equipment/process engineer in a semiconductor company, where she was involved in cross-functional team projects to drive improvements in yield and process productivity.
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Low Voltage Drives Report – 2021 Analysis
Analyzes global and regional LV drives market by 4 major product types and 39 discrete and process industries. Covers technical segmentation (i.e., power rating, voltage, sales channels, form factors, motor control, and network technology)
Report / 14 Sep 2021 / Joanne Goh
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These are Omdia driven recommendations based on content that is both similar, and has been frequently visited by other users in combination with the content you are currently viewing.
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These are Omdia driven recommendations based on content that is both similar, and has been frequently visited by other users in combination with the content you are currently viewing.
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