Phase 2


With a solid understanding of your needs, we can now explore potential solutions. There are a few core approaches, each with their pros and cons:

  • Building an in-house analytics platform allows full customization but requires more technical resources
  • Leveraging business intelligence software enables quicker dashboarding but may lack advanced capabilities
  • Moving to a cloud data platform provides scaling and reduces infrastructure burden but requires data migration
  • Using managed analytics services offers faster time-to-value but less control over models

Considering your budget, capabilities, and business priorities, we may recommend starting with a modern cloud data warehouse. This approach provides a scalable foundation for integrated performance data to enable advanced analytics.

Early wins include consolidated data access, improved query speed, and on-demand resources for ad hoc analysis. We can take an incremental approach – starting small and expanding over time.

We can also suggest complementing the data warehouse with BI software for consumable dashboards and visualizations. Longer-term managed analytics or dedicated data science resources can take things to the next level.

Balancing business needs with practical considerations like cost, speed, and capabilities is vital. At Databender, we aim to deliver maximum value through the right combination of technologies and services.

Interested in working with us?

Please reach out to learn what custom-built software, data, and AI tools can do for your business.