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LEAN Thinking for Big Data Analytics

Data managers must have the skills and knowledge to align their company’s vision with their data vision, to create inter operable data systems and enterprise-wide data architecture, to enforce data governance, and to manage artificial intelligence and machine learning for decision-making insights.

In 2011, the McKinsey Global Institute predicted that the United States would experience a shortage of 190,000 data scientists and 1.5 million managers and analysts capable of harvesting actionable insights from big data by 2018. With this explosion of data and analysts, it has become increasingly important for companies to hire managers capable of achieving business objectives by leveraging data best practices.

This course equips you with the knowledge and skills to transform your organization into a data-driven organization. By examining industry case studies, lessons learned, and the latest data analytics tools and platforms, you will learn how best to gain actionable insights from big data, as well as to develop data solutions and data transformation road maps for businesses of varying sizes and complexity levels.    

Topics Include:

  • Defining business objectives
  • Linking objectives with performance data
  • Data integration
  • Data standardization
  • Data architecture and rationalization
  • Process and system engineering requirements
  • Change management for data transformation
  • Data transformation case studies
  • Data governance and Chief Data Officer (CDO)
  • Data innovations and digital transformations
  • Artificial intelligence and machine learning for data managers
  • Current tools for data analytics
  • Decision-making and data visualization of uncertainties

Practical Experience:

  • Develop best practices for instituting data transformation
  • Learn to manage data talent and investments
  • Test state-of-the-art automation tools for data governance
  • Align a data vision with you organization’s mission and KPIs
  • Establish a road map for data applications and systems rationalization

Course Typically Offered: Online in Fall and Spring quarters.

Software: Tutorials of leading automation tools offered by Collibra, Informatica, SAP, and IBM will be available to students during this course; there is no additional charge for these.

Prerequisites: A bachelor’s degree or working experience in software programming, science, business management, or information science.

Contact: For more information about this course, please contact unexengr@ucsd.edu.

Course Number: CSE-41296
Credit: 3.00 unit(s)
Related Certificate Programs: Business Intelligence AnalysisSystems Engineering

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