I work for a Series B enterprise SaaS startup with ~100 employees and we've been seeing an increased dependency on data over time. For example, there is a clear need for -
* Reliable operating metrics that don't change based on who is tasked with querying for it
* Streamlining ad-hoc requests for product data for decision making / marketing
* Using skills-set (w.r.t. handling data) across teams more effectively
* Exploratory data analysis to find predictors for customer satisfaction in product usage data
* Exploration of how data could be used to help existing customers (e.g. dashboard with key metrics that lead to better outcomes)
These are just some examples, though for me they point towards a need for central data organization with specific sub-teams that are tasked with key business needs -- data engineering, business intelligence and reporting, analysis and exploration etc.
What is your take on this? Is this thinking aligned with what you've done at your organization? What are the issues that this might create?
* Reliable operating metrics that don't change based on who is tasked with querying for it * Streamlining ad-hoc requests for product data for decision making / marketing * Using skills-set (w.r.t. handling data) across teams more effectively * Exploratory data analysis to find predictors for customer satisfaction in product usage data * Exploration of how data could be used to help existing customers (e.g. dashboard with key metrics that lead to better outcomes)
These are just some examples, though for me they point towards a need for central data organization with specific sub-teams that are tasked with key business needs -- data engineering, business intelligence and reporting, analysis and exploration etc.
What is your take on this? Is this thinking aligned with what you've done at your organization? What are the issues that this might create?