From the course: The Data Science Playbook for Private Equity and Venture Capital
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Early success with data science
From the course: The Data Science Playbook for Private Equity and Venture Capital
Early success with data science
- [Instructor] As we embark on using data science in private equity and venture capital firms, it's important to be tactical. Aim for quick wins that can build a track record of success, and entice increased investments in data science. Earlier we discussed some of the barriers to success with data science, avoid them. Don't start with a huge data infrastructure project, a major software upgrade, or engage in battling any of the other major barriers to success. Going back to our lifecycle approach, we should look for small steps where we can have success. For example, at the early exploration stage, a small step is to explore additional data sources that can be used for identifying opportunities. At the due diligence stage, we should be examining what company data is available to validate growth and profitability assumptions and projections. Additionally, we should be searching for external data to inform those…
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