What is a data analytics strategy?
It is the plan that connects business objectives with data: what you want to decide, what data you need, how you integrate it and how you present it so people can act.What are the levels of analytics?
- Descriptive: what happened (dashboards).
- Diagnostic: why it happened.
- Predictive: what is going to happen (models).
- Prescriptive: what to do about it.
How do you implement enterprise data analytics step by step?
- Define the business questions and the KPIs.
- Integrate the data sources (one common model).
- Ensure data quality and governance.
- Build clear, actionable dashboards.
- Add predictive analytics where it adds value.
- Foster a data-driven culture across teams, key to closing the productivity gap.
Business Intelligence or Data Analytics?
BI focuses on describing what has happened with reports and dashboards; advanced analytics adds prediction and prescription. Most companies need both, in that order.Common mistakes
- Starting with the tool instead of the questions.
- Data in silos with no governance.
- Dashboards nobody uses.
- Not measuring the impact of decisions.
Frequently asked questions
Do I need a data warehouse to get started? Not always. You can start with a specific use case and build out the architecture as the need grows. How long does it take to see value? A first useful dashboard can be ready in weeks; data-driven maturity is an ongoing journey. Want your data to work for you? At BAOSS we design and implement your data strategy. Write to us.Prefer to talk to us directly? Contact the BAOSS team and tell us about your challenge.
