I help companies to make data-informed decisions to grow business. Provide an overview of product usage with relevant metrics and look for new opportunities for growth. Support planning with estimations based on historical data. Validate the hypothesis with experiments and learn more about users.To understand business and product performance, I start with a definition of metrics that measure what matters. It is helpful to understand the current state and opportunities to grow. The next step is creating data models, dashboards, and documentation, to make them accessible to everyone in the company. I have done a few iterations with activation metrics for Miro. Each time metrics changed with our understanding of users. It was helpful to coordinate the efforts of multiple teams across a company and detect opportunities for growth activation and revenue.I participate in all stages of the experimentation process from ideation to the learning summary. It lets me reduce the cost of experiments by validating basic assumptions with historical data, choosing the optimal metric and cohort of users for promising ideas, and optimizing analytics processes behind it. When we optimized the experimentation process within the activation team, we twice the number of experiments within a quarter. Moreover, my optimization of the process makes it simple for other analysts to pick up an experiment at any stage.I can help to transform raw data into a human-ready format and present it in business language. Speed up the analysis of open-question surveys with NLP methods. Analyze the user journey with process mining. Join together all the necessary information from hundreds of tables.There is no perfect data. There are no perfect metrics. To overcome this I use common sense, business understanding, empathy with users, and team support.