Data Analytics with Microsoft Excel

This expertly crafted course demystifies the Digital Analytics Framework and its pivotal role in modern business strategy. As data becomes increasingly vital in the corporate sphere, understanding how to capture, analyze, and leverage this data is crucial. Participants will explore the varying levels of data analytics, master the art of data visualization using pivot tables and charts, and learn how to make discerning color choices to convey information effectively.

From this foundation, the course advances into specific data analytics methods, where learners will discover frameworks for effective analysis, including comparison, ranking, trend and gap analysis, as well as specialized techniques like Pareto and cohort analysis. These methods are indispensable tools for interpreting data and influencing business tactics.

The journey through analytics delves into descriptive and predictive methods, focusing on the use of Excel's Data Analytics Tab. Students will gain expertise in employing regression analysis, choosing the correct variables, and establishing the best-fitting trend lines to predict future trends.

Lastly, the course culminates in a thorough understanding of prescriptive analytics and forecasting. Learners will be equipped with the skills to not only predict future trends but also recommend optimal actions, utilizing techniques such as moving averages and time series analysis to forecast with greater accuracy

Upon completion of the course, learner will

1. Gain proficiency in utilizing pivot tables and charts, selecting appropriate visualization tools, and refining data presentation aesthetics for impactful communication.
2. Develop the ability to apply structured analytical methods to business data, enhancing understanding of market trends, customer behavior, and operational performance.
3. Acquire the skills to execute regression analysis and predictive modeling, enabling the identification of significant variables and trends for informed business forecasting.
4. Learn to formulate prescriptive strategies and conduct forecasting analyses, using advanced techniques to project future business scenarios and outcomes.

1. Business strategists seeking to integrate data analytics into decision-making.
2. Data analysts aiming to refine their analytical techniques and reporting skills.
3. Marketing professionals looking to leverage data for targeted strategies.
4. Operation managers interested in data-driven methods for process improvement.
5. Financial analysts requiring advanced forecasting methods for financial planning.

Dwight graduated with a degree in Biotechnology (from NUS in 2001), Advanced diploma in Pharmaceutical management (from MDIS in 2007) and Masters in Education (from NTU in 2013). In 2014, Dwight ventured into Data Analytics and Database Management and picked up Statistics/Machine Learning, Big Data analytics, text mining & social media analytics and web applications. His other expertise includes data science programming languages such as R and Python. He is also deeply passionate in deep learning using sequential models and sequence to sequence models using Keras and h2oAI machine & deep learning platforms and libraries. He is also a Senior Data Analyst, where he performs data analytics and create predictive models using healthcare data.