In the last part of our series, we examine the detailed activities of an analytics team before, during, and after a sprint. You can compare your team’s work flow to the activities list in this article to see opportunities to become even more agile.
- By Stan Pugsley
- March 6, 2019
Working with data requires adaptation of many traditional agile techniques. How do we put agile practices and DevOps tools to use for analytics and data science projects?
- By Stan Pugsley
- March 5, 2019
Being aware of the limitations of modern techniques can help you avoid pitfalls in AI, machine learning, and data science.
- By Upside Staff
- March 5, 2019
Creating an agile analytics development environment is about much more than just tools. It is a combination of culture, practices, and tools that enable high productivity, high data quality, and maximum business value.
- By Stan Pugsley
- March 4, 2019
Thoughtspot CEO Sudheesh Nair explains why AI is the single most important emerging technology -- and why it's not enough for your success.
- By James E. Powell
- March 1, 2019
It's a challenge to find someone you want to hire, but once you find them, you still need to close the deal. Salary will be a major factor in your negotiations.
- By Lindsay Stares
- February 28, 2019
Pitfalls in using machine learning for scientific study, applications for AI in investment, carefully using AI in hiring.
- By Upside Staff
- February 28, 2019