Data analytics is transforming business processes at organizations large and small. As siloed data becomes more available through the deployments of environments such as data lakes and company-wide data warehousing, opportunities arise to apply analytics to improve efficiency, identify opportunity, and use predictions to take pre-emptive action. This course will introduce participants to the fundamentals of data analytics, big data frameworks, open source analytics tools, design methodologies, and visualization libraries through hands-on case studies.
Data scientists looking to expand their knowledge of data analytics techniques and tools. Also those working in social media, marketing, retail, and others looking to incorporate technology into their workplace.
How You Will Benefit
Provide the audience with an overview of industry-leading tools and methodologies for data analytics. Students will be able to:
Explain steps to clean and normalize data during fusion
Define the analytics pipeline of ETL, analyses, visualization, and reporting
Access data from traditional databases, document stores, Hadoop, and open APIs including open source data from social media (Twitter, Instagram, Facebook)
Map analytics application requirements to big data frameworks and tools
Utilize cloud-based tools, such as AzureML or Amazon Machine Learning Services, for real-time predictive modeling
Understand the limitations of data analytics algorithms
Integrate science and mathematics into business processes
Partner with Georgia Tech to hire a veteran. As a partner, the Georgia Tech program will train military members in areas that directly translate to their job duties.
Georgia Tech Professional Education allows working professionals and industry partners to access the expertise of a world-renowned technological research university. As an academic division of the Georgia Institute of Technology, we embrace the Georgia Tech values of integrity, excellence, impact, and innovation. These values drive every aspect of our programs.