Database Reference
In-Depth Information
12.1 Communicating and Operationalizing an Analytics
Project
As shown in
Figure 12.1
, the final phase in the Data Analytics Lifecycle focuses on
operationalizing the project. In this phase, teams need to assess the benefits of the
project work and set up a pilot to deploy the models in a controlled way before
broadening the work and sharing it with a full enterprise or ecosystem of users.
In this context, a pilot project can refer to a project prior to a full-scale rollout of
the new algorithms or functionality. This pilot can be a project with a more limited
scope and rollout to the lines of business, products, or services affected by these new
models.
Figure 12.1
Data Analytics Lifecycle, Phase 6: operationalize
The team's ability to quantify the benefits and share them in a compelling way
with the stakeholders will determine if the work will move forward into a pilot
project and ultimately be run in a production environment. Therefore, it is critical
to identify the benefits and state them in a clear way in the final presentations.
As the team scopes the effort involved to deploy the analytical model as a pilot
project, it also needs to consider running the model in a production environment for
a discrete set of products or a single line of business, which tests the model in a live
setting. This allows the team to learn from the deployment and make adjustments
before deploying the application or code more broadly across the enterprise. This
phase can bring in a new set of team members—namely, those engineers responsible
for the production environment who have a new set of issues and concerns. This
