Database Reference
In-Depth Information
2.2 Phase 1: Discovery
The first phase of the Data Analytics Lifecycle involves discovery (
Figure 2.3
). In
this phase, the data science team must learn and investigate the problem, develop
context and understanding, and learn about the data sources needed and available
for the project. In addition, the team formulates initial hypotheses that can later be
tested with data.
Figure 2.3
Discovery phase
2.2.1 Learning the Business Domain
Understanding the domain area of the problem is essential. In many cases, data
scientists will have deep computational and quantitative knowledge that can be
broadly applied across many disciplines. An example of this role would be someone
with an advanced degree in applied mathematics or statistics.
These data scientists have deep knowledge of the methods, techniques, and ways
for applying heuristics to a variety of business and conceptual problems. Others in
this area may have deep knowledge of a domain area, coupled with quantitative
expertise. An example of this would be someone with a Ph.D. in life sciences.
