Data Science & Big Data Analytics for Business Transformation
Course Overview
Businesses are increasingly looking to take advantage of Big Data to be competitive. In addition to Data Scientists organizations need data-savvy business leaders who can identify opportunities to solve business problems using advanced analytics and who have the expertise to lead an analytical team. This course gives business leaders the skills and knowledge to better manage such analytical efforts. It describes how to get started and what is required to effectively run projects which leverage Big Data analytics. Specifically it addresses: deriving business value from Big Data leading Data Science projects using a data analytics lifecycle developing Data Science teams and driving innovation using analytics.
At the end of the training, participants will be able to:
- Articulate the business value of Big Data and the opportunities it presents to drive growth and innovation
- Discuss key Data Science analytic methods and identify opportunities for applying these methods
- Lead analytics projects using a structured lifecycle approach
- Develop Data Science teams to leverage the required skill sets and appropriate organizational models
- Drive innovation via analytics projects by understanding how to drive organizational change
Pre-requisite
- Experience managing teams or leading initiatives
- High-level understanding of quantitative methods used in business performance measures
Duration
2 days
Course Outline
- Overview of Data Science and Big Data analyticsn
- Business drivers for advanced analyticsn
- Stages of analytical maturity in an organization
- Business value of a Data Science projectn
- Overview of key advanced analytic techniques and their applicationsn
- Big Data tools and technologies
- Overview of data analytics lifecyclen
- Frame a business problem as an analytics problemn
- Four main deliverables in an analytics project
- Develop an analytic team, roles and skill setsn
- Four approaches to develop Data Science capabilitiesn
- Three organizational models for Data Science teams
- Cultivate characteristics of visionary thinking to apply to Data Science teamsn
- Incorporate change management as part of implementing a data-driven approach to decision makingn
- Leverage small wins to change how the organization approaches problems
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