Analytics for Business: Discovering Insights from Data
May 31, 2021 - June 18, 2021
May 31, June 4, 7, 11, 14, & 18, 2021
Mondays & Fridays
4:00 pm - 7:00 pm
Synchronous sessions via Zoom
Asynchronous sessions via access to the AteneoBlueCloud (Canvas LMS)
Early Eagle Rate:
May 17, 2021
In the age of big data, it is almost effortless to obtain information and data sets that can be helpful in improving our strategies and making a decision. But the amount of data available can also be overwhelming and confusing. Examining, analyzing, and presenting the data, with only a minimal understanding of the right methods and tools, can result in misleading presentations and futile strategies.
As we progress in this Digital Economy, everyone should be able to effectively collect and structure applicable meaning from data and translate it into a compelling presentation.
This program combines the basics of data analytics such as methods for analyzing and using statistical data; and the fundamentals of data and results presentation through the use of appropriate visual representation including frequency tables, charts, scatterplots, among others.
Who should attend
This program is ideal for professionals, executives, managers, data analysts, and support staff from Operations, R&D, Marketing, Sales, Finance, and HR who are involved in presentations that may relate to performance, trend analysis, budgeting, forecasting, and others.
After the course, you will:
- Apply appropriate methods in analyzing, presenting, and using relevant data;
- Learn how to translate applicable data into the appropriate visual representation; and
- Effectively communicate and present the most relevant information
I. Planning for Data Analysis
Covers the concepts in data analysis (qualitative and quantitative research), its cycle and steps. This includes data validation and cleaning of sample types of data.
II. Techniques for handling and analyzing data
Covers various techniques on analyzing high volume and high dimension of business data.
III. Data Analysis
Covers discussions on statistical significance, descriptive analysis and statistical models and practical applications of analysis tools on sample data. This will also include examples and activities on the usage of the Statistical Models (T-Test, ANOVA, Chi-Square) for hypothesis testing
IV. Presentation of Findings
Covers the how's on presenting Data Using Frequency Table, Charts and Graphs, presenting Summary of Findings, Presenting Conclusion and Recommendations, and tips in Writing/Organizing a comprehensive Output
Mr. Charles Benedict Chan is the General Manager of Neural Mechanics Inc. handling the company’s diverse set of Artificial Intelligence and Machine Learning based products.
He started his professional career in Globe Telecom as a Business Management Associate and eventually moved on to become a Senior Product Manager handling Value Added Services and Convergent Services for Globe Broadband. He then transferred to Singapore to work for Procter and Gamble as a Regional Assistant Brand Manager handling multi-million dollar brands such as Pantene shampoos and Joy Dishwashing. He has also experience working for smaller, struggling brands including Braun beauty and grooming, and Fairy Dishwasher Tablets.
Mr. Chan earned his Bachelor’s degree in Marketing from the University of the Philippines – Iloilo Campus.
Ms. Maria Isabel Saludares holds a Master of Science in Physics degree and is currently a PhD Student in Computer Science from the University of the Philippines - Diliman. Her expertise is on video and image processing and is currently affiliated with the Computer Vision and Machine Intelligence Group (CVMIG) from the same university. Her work experience spans several computer vision applications such as coral reef coverage and assessment, medical image analysis, detection and tracking, and 3D modeling and visualization. She has also done several text analytics using natural language processing focusing on social media listening. Presently, she oversees several AI projects working together with several data scientists and developers in Neural Mechanics Inc.