Data Panda brings the Microsoft SQL Server databases behind your applications together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.
Microsoft SQL Server is the enterprise relational database behind a very large share of .NET applications, Dynamics 365 deployments and internal systems built inside Microsoft-first organisations. It runs on-prem and on Azure, and usually holds the operational data that matters most to the business: orders, transactions, schedules, customer records.
The point of pulling SQL Server into a warehouse is that reports written directly against the production database age badly. Schemas drift with every release, big joins compete with live traffic, and the ETL someone built five years ago has become the thing that no one wants to touch. In a warehouse, SQL Server joins Dynamics 365, Business Central, Shopify and the accounting ledger without putting reporting load on the system that has to stay up.
Application data joined to Dynamics, BC and the rest of the stack, without queries on production.
Let SQL Server changes drive the rest of the stack.
Score, classify and forecast on data the application already writes.
Internal tools on SQL Server data without sharing SA credentials.
A list of concrete reports, automations and AI features we have built on MS SQL Server data. Pick the one that matches your situation.
Are our dashboards running directly on production SQL Server?
A survey of which dashboards query SQL Server directly, with load, query cost and risk flagged. Highlights the reports that will time out at the next traffic spike and the reports that should move to the warehouse first.
What changes when the application ships a new release?
Schema change log with added, renamed and removed columns, linked to the dashboards that use each. The release conversation stops breaking reporting quietly on a Tuesday deploy, because the impact is visible before the migration runs.
How do we report on app data without developer time?
Tables land in the warehouse with joins to CRM, accounting and Microsoft stack already wired, so business users query with SQL or BI tools instead of asking engineering for one more extract.
Revenue and transaction data from the app joined to the accounting ledger, without reporting load on production. Subscription, usage-based and transactional revenue tie back to the same customer record.
Product usage and transaction signal on every CRM account, sourced from SQL Server. Reps see the account about to expand and the one going quiet before the renewal call.
Schema drift, data-quality gaps and load shifts monitored in one place. Reporting stops being a surprise every release and becomes part of the deploy check.
The .NET application's SQL Server tables join Business Central entities on the same customer, order and item keys in the warehouse. Reporting reads one consistent customer record across both, without a SQL Server linked server in production.
App-level signals from SQL Server push onto Dynamics 365 account and contact records as custom fields and timeline activity. Sales sees product usage on the record without the warehouse table needing to be re-exposed to production.
Customer records from the SQL Server application are matched to Salesforce accounts on email domain and external id. Account owners see app behaviour on the Salesforce record, without a separate Microsoft-to-Salesforce pipeline.
Invoices generated inside the SQL Server-backed application post to Exact Online with customer, VAT and ledger coding resolved. The app keeps its invoicing logic and finance still gets clean sales journal entries.
You keep the reporting tool you already have. We connect it to the warehouse where your MS SQL Server data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
The default path is change-data-capture or log-based replication against a secondary replica so reporting workload never touches the primary. For smaller databases, scheduled incremental sync on an updated-at column is used instead. The load profile is tuned to the tenant.
Schema changes are tracked and versioned in the warehouse. Added columns appear on the next sync, renamed ones are linked to their history and removed columns stay read-only so older reports still run. Dashboards that depend on a removed column are flagged instead of silently returning null.
We review your MS SQL Server setup and the systems around it. Together we pick the first thing worth building.