Cloud Migration Consulting Services
Customer story
Coffee retailer accelerated financial reporting with Snowflake
Snowflake Data Cloud turned weeks of reporting into minutes.
Pythian deployed a Snowflake Data Cloud on Azure, replacing manual spreadsheets with near real-time POS analytics across 400+ stores.
A fast-growing regional coffee company with over 400 locations across 11 states faced severe reporting bottlenecks when its aging on-premises SQL Server couldn't handle surging transactional data from a new Xenial POS system. Finance analysts spent up to two weeks compiling giant Excel spreadsheets just to get basic performance numbers, while the lean internal IT team lacked the cloud expertise to execute a migration independently. The retailer turned to Pythian for strategic guidance and hands-on cloud implementation, deploying a Snowflake Data Cloud hosted on Microsoft Azure integrated with Power BI. Today, finance analysts leverage near real-time insights across over half a billion POS records, shifting their time from manual compilation to evaluating store profitability and advising executive leadership.
The transition to Snowflake on Azure transformed how we operate. What used to take weeks of manual work in Excel is now automated, giving leadership near real-time visibility from company-wide overviews down to individual drink orders across all 400+ locations ."
VP of Finance & FP&
Regional Coffee Company
500M+
POS records analyzed
100%
Reduction in manual reporting
400+
Store locations on one platform
Accelerate your financial reporting with modern cloud data warehousing.
Rapid store growth outstripped aging on-premises database architecture.
Pythian migrated historical and live POS data from SQL Server to Snowflake Data Cloud on Azure, integrating Power BI to deliver near real-time analytics across 400+ stores.
Our legacy SQL Server couldn't handle transaction surges, forcing analysts to rely on two-week-old spreadsheet reports. Pythian delivered a modern Snowflake architecture on Azure that eliminated our reporting backlog without straining our lean IT team ."
VP of Finance & FP&A
Regional Coffee Company
SQL Server couldn't handle modern data volumes
The on-premises database was built for a smaller operation and buckled under the data load generated by 400+ store locations running a new POS system.
Weeks lost to spreadsheet compilation
Finance analysts spent their time importing raw data into giant Excel files instead of interpreting reports and advising the business.
Internal team lacked migration experience
With only a handful of IT staff and minimal cloud knowledge, the company needed an experienced partner to guide the transition with confidence.
Cloud usage went unmeasured and unallocated
IT had no way to monitor resource consumption by department or charge back computing costs, making budgeting and accountability difficult.
Pythian identified and prioritized the company's core business needs.
Pythian ran a collaborative workshop with finance and IT stakeholders to identify and prioritize business needs. The session surfaced requirements around real-time data access, Power BI compatibility, cost chargebacks, and ease of use. Pythian then provided a decision-tree to help the company select the right cloud platform.
Historical POS data was unified across all 400+ locations.
Pythian built a flexible data model and migrated historical sales data from the company's previous and current Xenial POS systems. The data spanned more than 400 locations across 11 states. Engineers normalized and transformed records into a consistent, analysis-ready format.
The team deployed a cloud platform that runs without a dedicated DBA.
A Snowflake Data Cloud hosted on Microsoft Azure complemented the company's existing infrastructure. The platform leveraged familiar tools like Active Directory for user controls and required no in-house database administrator, making it ideal for a lean IT team.
Pythian ensured analysts could access data in their preferred formats.
As the finance team started pulling reports through Power BI and direct Snowflake exports, Pythian fine-tuned the platform iteratively. Adjustments ensured that every analyst, regardless of technical skill level, could access the data they needed in the format they preferred.
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