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Course

LEAN Thinking for Big Data Analytics

CSE-41296

According to the Bureau of Labor Statistics most recent figures, overall employment of mathematicians and statisticians is projected to grow 30 percent from 2018 to 2028 - much faster than the average for all occupations. Businesses will need these workers to analyze the increasing volume of digital and electronic data. With the 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 will equip you with the knowledge and skills required to pivot your workplace 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.

Course Highlights:

  • 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
  • Current tools for data analytics
  • Decision-making and data visualization of uncertainties

Course Learning Outcomes:

  • 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 winter 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 Information

Online
3.00 units
$795 - $895

Course sessions

Closed

Section ID:

184041

Class type:

Online Asynchronous.

This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

Textbooks:

No textbook required.

Policies:

  • No refunds after: 9/30/2024

Schedule:

No information available at this time.
Closed

Instructor: James Meng

James Meng
James C.S. Meng, Ph.D., MSM is a currently a senior fellow at UC San Diego – Super Computer Center and a visiting scholar at Massachusetts Institute of Technology - Sloan School of Management. Dr. Meng held various positions with the federal government’s senior executive service from June 1998 until June 2015 when he retired as deputy assistance secretary of the Navy, Business Enterprise Solutions. Dr. Meng has a B.S. in mechanical engineering from Taiwan University, an M.S. in engineering physics from UC Berkley, an M.S. in management from the Massachusetts Institute of Technology - Sloan School of Management and a Ph.D. in aeronautical engineering from UC Berkley.

Dr. Meng is an established author with numerous articles published in various journals including the Journal of Fluid Mechanic, Journal of Applied Optics and Journal of Computational Physics. He has published technical reports on laser doppler velocimetry, superconducting electromagnetic thruster (SCEMT ), electric propulsion technology, experimental studies of turbulence reduction, simulations of hydrodynamics wake in oceanic environment, theoretical analysis of internet waves, and hypersonic reentry vehicle dynamics. In addition, Dr. Meng has obtained six patents in SCEMT, elecomagnetohydrodynamic boundary layer control and acoustic remote cavitation.
 
Full Bio
Add To Cart

Section ID:

185656

Class type:

Online Asynchronous.

This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

Textbooks:

No textbook required.

Policies:

  • No refunds after: 1/13/2025

Schedule:

No information available at this time.
Add To Cart

Instructor: James Meng

James Meng
James C.S. Meng, Ph.D., MSM is a currently a senior fellow at UC San Diego – Super Computer Center and a visiting scholar at Massachusetts Institute of Technology - Sloan School of Management. Dr. Meng held various positions with the federal government’s senior executive service from June 1998 until June 2015 when he retired as deputy assistance secretary of the Navy, Business Enterprise Solutions. Dr. Meng has a B.S. in mechanical engineering from Taiwan University, an M.S. in engineering physics from UC Berkley, an M.S. in management from the Massachusetts Institute of Technology - Sloan School of Management and a Ph.D. in aeronautical engineering from UC Berkley.

Dr. Meng is an established author with numerous articles published in various journals including the Journal of Fluid Mechanic, Journal of Applied Optics and Journal of Computational Physics. He has published technical reports on laser doppler velocimetry, superconducting electromagnetic thruster (SCEMT ), electric propulsion technology, experimental studies of turbulence reduction, simulations of hydrodynamics wake in oceanic environment, theoretical analysis of internet waves, and hypersonic reentry vehicle dynamics. In addition, Dr. Meng has obtained six patents in SCEMT, elecomagnetohydrodynamic boundary layer control and acoustic remote cavitation.
 
Full Bio