Work with DataHub

Working with DoiT DataHub typically involves the following stages:

Data discovery. Identify internal and external data sources based on your goal.

For example, to measure profitability on a per unit basis (unit economics), you may need revenue data, cost of goods sold (COGS), customer acquisition costs (CAC), and customer lifetime value (CLV). The data is likely to reside in various locations and with different teams, even outside of your organization.
Data extraction and validation. Collect only the data you need from relevant source systems; check the accuracy and consistency of the data to ensure that the data is valid and suitable for further analysis .
Metric and dimension modeling. Determine which labels, dimensions, and metrics to send to ensure the reports align with your use case.

Start by reviewing the data you plan to import and considering how you'd like to structure your reports. From there, you can determine which dimensions and values to include. Setting an appropriate level of data granularity not only helps effective analysis but also mitigates the risk of unintended data disclosure.
Data transformation and data loading. Send your data to DoiT DataHub.
- You can import data using the DataHub API or CSV files.
- Make sure to sanitize your data, for example, mask personally identifiable information (PII), before sending it to DoiT.
Data analysis and visualization. Leverage the rich FinOps features of DoiT Cloud Intelligence to gain visibility into various aspects of your organization and turn data into actionable insights. For example, reports, Attributions, Attribution groups, Cost splitting, and custom dashboards.
Policy and governance. Establish policies and governance mechanisms to maintain optimal cloud usage and cost efficiency. For example, create alerts to track your metrics and get notified of important events and conditions, set budgets to track actual spending against planned spending and ensure accountability and predictable financial outcomes.