Assume you have made the choice: You are going to deploy and use a new analytical software product in your organization. How do you get things going? Transitioning from one analytical software platform to another requires thoughtful consideration and strategic planning to ensure the success of your migration project. What specific aspects should you consider when embarking on this journey?
The Users
The analytical software supports and enhances the work of the users in their respective fields. It is crucial to understand what these users do and what their expertise (esp. regarding software) is.
Use Cases
It is relevant to understand what the users are actually doing with “data analytics”. What analytical methods do they apply? What domains of applied data science are they using? Are there specific needs inside such domains?
Analytical Artifacts
Data science and analytics use cases are usually constructed using reusable “building blocks” that are able to serve multiple use-cases. These “building blocks” also known as analytical artifacts are elements in the analytical process that are applied/ implemented by the users, or automatically. They can be data connections, predictive models, code snippets, decision rules, or even be encapsulated procedures as a combination of said artifacts, and more.
The Architecture
The current setup of analytical processes can be thought of as an analytical architecture that is demanding a thorough comprehension for effective utilization and enhancement.
Documentation, Manuals, Templates
Besides the analytical artifacts (being used in analytical processes) organizations accumulate documents that are used to assist with the software or describe how the system is set up and supposed to work.
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You and your organization are unique. The outline above shows you what to consider, but what we need to do depends on you and the outcome of this discussion. We will gladly assist you in such a migration project!
