$2,090.97 – $6,063.87

BUSINESS ANALYTICS (BA): DATA DRIVEN DECISION MAKING (2 DAYS LEADERSHIP MA...

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Location

Marina Bay Sands Singapore

10 Bayfront Avenue

Singapore, 018956

Singapore

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Refunds up to 30 days before event

Eventbrite's fee is nonrefundable.

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Description

WHAT YOU WILL LEARN
Business Analytics uses statistical, machine learning, operations research and management tools to drive business performance. Companies such as Amazon, Google, HP, Netflix, Procter and Gamble and Capital One uses analytics as competitive strategy. The course is designed to provide in-depth knowledge of handling data and Business Analytics’ tools that can be used for fact-based decision-making using real case studies.

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WHO SHOULD ATTEND

This workshop series is suitable for business and technology professionals, leader, director, executive, CSO, CXO,CMO, CIO, CTO, CDO, CFO, COO, CMO, and CEO.

FOR LEADERS

Gain a working knowledge of data science, which will enable leaders to identify the challenges that analytics, machine learning, and artificial intelligence can solve. It will also help them make the most effective investments in people, data, systems, culture and organizational structure.

FOR INNOVATORS

Explore what a sound data analytics strategy can do for you. Together, we’ll experiment, explore and embrace business innovation opportunities for growth in familiar - and completely new - areas to help you do more than you ever imagined possible.

FOR PROFESSIONALS

Business Analytics may be thought of as a series of skills, technologies, processes and tools by which we can analyse and convert data not just into management information but into predictive insights and business intelligence (BI). Move beyond reporting what is happening and into why things are happening and consequently what might happen in the future.

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AGENDA

Module 01: Business analytics as a competitive strategy.

• Differentiate business intelligence (BI) from business analytics & decisions.

• Set objectives, use case and goals.

• Define criteria for success and failure.

• Select methodology and data.

• Identify relevant internal and external factors.

• Validate models using predefined success and failure criteria.

Module 02: Analyzing data using statistical learning and machine learning algorithms.

• Differentiate machine learning from statistics.

• Choose between statistical modeling and machine learning.

• Use statistical methods in a machine learning project.

Module 03: Data visualization & storytelling through data.

• Understand the importance of context and audience.

• Pick the best data visualization format for your story.

• Recognize and eliminate the clutter.

• Direct audience to the most important parts of your data.

• Utilize the concepts of design in data visualization.

Module 04: Descriptive, predictive and prescriptive analytics techniques and tools.

• Learn from past behaviour to influence future outcomes.

• Identify risk or opportunities in the future.

• Foresee what will happen and when will it happen.

• Provide recommendation on how to act upon to take advantage of predictions.

Module 05: Supervised & unsupervised machine learning algorithms.

• Classification and regression supervised learning problems.

• Clustering and association unsupervised learning problems.

• Example algorithms used for supervised and unsupervised problems.

• Understanding semi-supervised learning.

Module 06: Analyze and solve problems.

• Analytical and creative thinking in problem solving.

• Systematic process of problem solving.

• Define the issue & focus on the “drivers” behind issues.

• Creative problem solving technique.

• Pareto Analysis in deciding what critical problems to address first.

Module 07: Analyse and solve problems from different industries such as manufacturing, service, retail, software, banking and finance, sports, pharmaceutical, aerospace, etc.

Advancement in technology and changing needs of the traditional business department.

Predictive insights: Combining internal and external business information.

News analysis (web scraping) and sentiment analysis.

Module 08: Big data analytics tools, application and best practices.

• Steps to creating effective analytics program.

• Managing data scattered silos across various units.

• Customer and product data.

• Data governance and IT governance.

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Date and Time

Location

Marina Bay Sands Singapore

10 Bayfront Avenue

Singapore, 018956

Singapore

View Map

Refund Policy

Refunds up to 30 days before event

Eventbrite's fee is nonrefundable.

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