Read the 2-pager by Ganesh Mani here: http://bit.ly/2TvfbnW
Data Supply Chain Management is the collection, organization, flow and streamlining of data – including any pre-processing and normalization steps - to make it usable, guided by domain knowledge, for the next downstream process. Typically, this next step involves analysis via traditional statistical or contemporary machine learning tools. The end goal of the exercise is to generate insights that can imply customer value, inform revenue or pricing metrics, optimize costs and help gain a competitive advantage in the marketplace.
In particular, this webinar will discuss:
TYPES OF DATA
- Human vs. machine-generated
- Passive vs. active (incl. proactively collecting additional elements)
- Numbers, text, audio-video (incl. derivatives/summaries of them)
- Base vs. Meta
- By location / geography
- By demographics
FINANCIAL DATA SOURCES
- Govt. / Exchange-derived
- Company-generated and reported (to the regulators)
- Other (incl. alternative data sources)
WHY THE BUZZ AROUND ALTERNATIVE DATA?
- The promise of an “edge”
- The plethora of new sources (which is good and bad)
- Focus on additional decision dimensions: e.g., ESG
For a traditional or alternative portfolio analyst, it can help with security selection, asset allocation, and risk management tasks.
Our conversation will last approximately 35 minutes with the remaining time for Q&A.
This session will be recorded, and the recording link will be sent to those who have registered for the webinar.