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The unexpected in data analysis is interesting
The data analyst's mission changes during each phase in a new business.
Sometimes they play a role like a BI operator, and other times they work with development and planning team, to build a performance measurement framework, and conduct scientific experiments.
In addition, as phase progresses, you will also be required to face the data with a broader perspective.
As a data-driven product owner, it is an important mission to overlook the whole picture of the business to find potential issues related to the OKR and to find new growth indicators.
Sometimes something completely unexpected will be used as a very important variable, and that's also what makes it interesting.
Methods and algorithms are constantly updated.
It's not just all about current phase. In order to expand the business, it is necessary to create a process for both strategy and algorithm design, by combining the analysis of each phase.
As we launch new businesses that are constantly subject to change and often remain unknown, we must constantly check the correlation between algorithmic indicators and variables and our business goals, and then present new targets and growth indicators.
It's easier said than done. The reality is that things don't always go the way you want them to, but little by little we'll get closer to the ideal of analyst.
The real pleasure of creating analytical models
Primal G's strength is business model hatching, as a data analyst, our responsibility is to run analytical models alongside it.
Rather than analyzing as a task, we need to understand the entire business and constantly consider how to analyze it, so we build our own analysis models and even data warehouses by ourselves.
This is possible because we are involved in a new business, and I think it is very rewarding.