Data & Analytics Case Study

Data & Analytics Program Modernization for a Global Restaurant Group

Client

Our client is a leading American-based restaurant company best known for its popular fast-casual Asian chain. The company operates thousands of locations worldwide with 3 globally recognized brands and emphasizes a commitment to family values, quality ingredients, and customer satisfaction.

CLIENT PROFILE
EMPLOYEES: 50,000+
INDUSTRY: Food Service
FOUNDED: 1973

Project Scope

Relying on a Data & Analytics program that was lagging behind

The restaurant group was looking for assistance uncovering weaknesses in their data & analytics program as well as recommendations on how to resolve these issues from an outsider’s perspective. The company at the time had an on-prem data warehouse and utilized MicroStrategy and Netezza for much of their BI and analytics.

Smartbridge has extensive experience in data & analytics modernization

Key Challenges

Carefully managing large amounts of data and balancing self-service analytics

Throughout any project, there are always a few challenges that the Smartbridge team faces. Some of these are more common than others, but all allow our consultants to display their talents and resourcefulness. Here are a few the team encountered for this particular project and what it meant in regards to their work:

  • The volume of data. Due to the size of the client, they have an immense amount of data such as store transactions, client and customer surveys, HR data, etc. Smartbridge had to be meticulous while performing data loads and making sure sequences were done correctly to ensure everything is functioning as it should. The team needed to be sure they worked through the most efficient way to design data transfer and extraction processes.
  • Some of the technology the client uses for certain activities is legacy or highly custom which can be a little more complex and something the Smartbridge team needed to account for while preparing to move the client from an on-prem data warehouse to a cloud data warehouse.
  • The last challenge Smartbridge encountered was finding the right balance of self-service analytics for a client of this size. Smartbridge and the client worked together to fine-tune what dashboards and analytics would be managed by the company’s internal information services team and what would be managed by the departments themselves.

The Smartbridge Solution

Modernizing the data warehouse and improving BI analytics

Smartbridge conducted a full current state data & analytics assessment for the client which consisted of interviewing 50 employees across 20 departments, analyzing their business intelligence & analytics tools, and reviewing their data architecture and data flows. Through this, Smartbridge identified multiple gaps and pain points with their current data & analytics systems and processes. The team then provided a comprehensive future state vision and technology recommendations which included implementing Microsoft Power BI as their enterprise BI & analytics tool.

A full breakdown of the objectives achieved were:

  • Implement the future state technology and migration path for Netezza/Informatica data warehouse environment.
  • Enable self-service analytics to the business analysts and other business users
  • Guide the establishment of a Data, Analytics and BI Center of Excellence (COE) and data governance processes.
  • Establish the Power BI framework and best practice for use as the enterprise BI tool while assessing the longer-term viability of MicroStrategy for operational reporting.
  • Build tables and pipelines needed to ingest additional data into the Azure Synapse data warehouse including SSIS Fin data mart conversion, Netezza native data extract conversion, Workday HR data and Guest Data.
  • Convert reports from MicroStrategy to Power BI.
  • Build new reports in Power BI per business requirements.

Technologies Used

Azure Synapse
power bi partner

Value Delivered

Data is easily accessible and reporting is a breeze

With Smartbridge’s assessment and recommendations, the client can simplify insights, account for users with varying analytics capabilities and experience, combine different data sources for ad-hoc analysis, and create a centralized location to build and share dashboards and insights.

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