Data Science and Big Data Analytics for Business Transformation Eğitimi

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Data Science and Big Data Analytics for Business Transformation

Learn how to use advanced analytics to identify business opportunities and solve problems.

Business organizations need leaders who can use data analytics to solve business problems and lead a big data analytics team. This course teaches you the requirements for managing big data analytics projects and how to start them.

What You'll Learn

  • The business value of big data and opportunities to drive growth and innovation
  • Apply data science analytic methods and identify opportunities for applying these methods
  • Employ a structured lifecycle approach to lead analytics projects
  • Leverage the skill sets and appropriate organizational models required to develop data science teams
  • Use analytics projects to drive innovation by understanding how to affect organizational change

Who Needs to Attend

  • Business leaders wanting to enhance analytics-driven decision making
  • Managers looking to build a new analytics or data-science capability
  • Leaders of business-intelligence or operations teams looking to raise the level of analytics

Prerequisites

  • Experience in managing teams or leading initiatives
  • High-level understanding of quantitative methods that measure business performance

Follow-On Courses

There are no follow-ons for this course.

Course Outline

1. Introduction

  • Overview of data science and big data analytics
  • Business drivers for advanced analytics
  • Stages of analytical maturity in an organization

2. Deriving Business Value from Big Data

  • Business value of a data science project
  • Overview of key advanced analytic techniques and their applications
  • Big data tools and technologies

3. Leading Analytic Projects

  • Overview of data analytics lifecycle
  • Frame a business problem as an analytics problem
  • Four main deliverables in an analytics project

4. Developing Data Science Teams

  • Develop an analytic team, roles, and skill sets
  • Four approaches to develop data science capabilities
  • Three organizational models for data science teams

5. Driving Innovation via Analytic Projects

  • Cultivate characteristics of visionary thinking to apply to data science teams
  • Incorporate change management as part of implementing a data-driven approach to decision making
  • Leverage small wins to change how the organization approaches problems



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