Introduction to Data Analytics in Decision Making


Data Analytics pertains to the concept of gathering and analyzing the raw data in order to see the trends or patterns and draw conclusions from the given data. Data analytics is utilized to aid companies and businesses in optimizing their performance, efficiency, profit maximization, and better decision-making strategies. Nowadays, the techniques and processes of data analytics are aided by a variety of software tools such as data mining programs, open-source languages and data visualizations.

Presently, a lot of companies and businesses are utilizing data analytics in order to analyze the information they gather and develop better business strategies based on the information available. This is due to the fact that if used wisely, data analytics can provide companies with a competitive advantage against competitors in the industry since the company can identify new opportunities to which they can develop business strategies from the new trends and capitalize on it. Because of the high level of competition in the market, companies understand the importance of data analytics and how it allows them to stay competitive in the market and develop better decision-making strategies.

At the end of the session, the participants shall be able to:

1. Help participants identify problems where analytics can help in terms of modeling, simulation or prediction;

2. Provide participants the conceptual understanding and share experiences on the applications of data analytics; and

3. Provide a clear understanding of why companies see data analytics essential to the delivery of their products and services.


  • Approaches to Business Decision Making
  • Visual Analytics
  • Business Intelligence Tools
  • Data Visualization
  • Dashboard Development
  • Optimation and Simulation
  • Discrete Event
  • Process simulation
  • Dynamic Simulation
  • Statistical Modeling and Time Series Models
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Text Analytics
  • Data Analytics in Different Sectors
  • Analytics for Products and Services
  • Users of Data Analytics
  • Google
  • LinkedIn
  • Amazon
  • Media and Entertainment
  • Education
  • Healthcare
  • Government
  • Weather Forecasting
  • Europe-PH News

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