Discover how we streamlined data processing: from hundreds of CSVs to one semantic layer. Explore our business case!

If you are working with large and complex datasets, you know how challenging it can be to manage and analyse them using traditional tools like spreadsheets. CSV files are a common format for storing and exchanging data, but they have many limitations and drawbacks. They are prone to errors, inconsistencies, duplication, and corruption. They are hard to read, understand, and manipulate. They require manual intervention and tedious processes to extract, transform, and load (ETL) them into a database or a reporting tool and they are not scalable or secure for enterprise-level data needs.

That’s why many organisations are looking for a better way to handle their data and turn it into actionable insights. One of the most effective solutions is to use a semantic layer, which is a logical representation of the data that abstracts the underlying complexity and provides a common language and structure for users to access and analyse the data. A semantic layer acts as a bridge between the raw data sources and the end-user applications, such as dashboards, reports, or visualizations. It simplifies the data by organizing it into meaningful concepts, categories, and relationships that reflect the business context and goals. It also enables self-service analytics, allowing users to create their own queries and reports without relying on IT or technical skills.

A great example of how a semantic layer can transform data management and analytics is the case of a large QSR (quick service restaurant) brand in Asia, which operates over 1000 outlets. The brand was facing a huge challenge with its data, as it had to deal with over 300 daily CSV extracts from various sources, such as point-of-sale systems, loyalty programs, customer feedback and third-party vendors. The CSV files were inconsistent, incomplete, and inaccurate, making it difficult to consolidate and reconcile them. The brand had no visibility into its performance, customer behaviour, or market trends. It was losing time, money, and opportunities due to poor data quality and availability.

With the help of Rapida Solutions the brand decided to implement a semantic layer solution that would enable it to access and analyse its data in a fast and easy way. The solution involved modelling the data using a tool called PowerBI Desktop, which is a powerful and intuitive data visualization and analysis software. PowerBI Desktop allows users to connect to various data sources, shape and transform the data using simple drag-and-drop operations, and create stunning reports and dashboards with interactive charts, maps, tables, and filters. The semantic layer created by PowerBI Desktop consists of three components: queries, which define how to retrieve the data from the sources; data model, which defines how to organize the data into tables, columns, measures, and relationships; and report canvas, which defines how to display the data in visual elements.

Using PowerBI and the industry-based experience Rapida Solutions were able to create a comprehensive semantic layer that covered all aspects of its business operations and objectives. The semantic layer included metrics such as sales revenue, transactions, average check size, product mix, etc. The semantic layer also included dimensions such as outlet location (country/region/city), outlet type (drive-thru/dine-in/delivery), time period (day/week/month/year), product category (food/beverage), product name etc. The semantic layer enabled the brand to perform various types of analysis on its data such as:

• Comparing sales performance across outlets
• Identifying best-selling products
• Analysing customer preferences
• Evaluating marketing campaigns
• Detecting anomalies
• Forecasting demand
• Optimizing inventory
• Improving customer service
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The semantic layer solution also allowed the brand to publish its reports and dashboards to PowerBI Service (a cloud-based platform that hosts PowerBI content) where they could be accessed by authorized users from any device (desktop/mobile/web). The users could also refresh the data on demand or on schedule using PowerBI Gateway (a software that connects PowerBI Service to on-premises or cloud-based data sources). The users could also share their reports and dashboards with others using PowerBI Apps (a collection of related reports that can be distributed within an organization).

The benefits of the semantic layer solution were immense for the brand. It was able to transition from CSV chaos to semantic simplicity in a matter of weeks. It was able to reduce its ETL processes from hours to minutes. It was able to improve its data quality and accuracy significantly. It was able to gain insights into its business performance that were previously unavailable or hidden. It was able to empower its users with self-service analytics capabilities that enhanced their productivity and decision-making. And it was able to achieve all this with minimal IT involvement and cost.

The case of the QSR brand in Asia is just one example of how the Rapida Solutions semantic layer can revolutionize data management and analytics for any organization that deals with large and complex datasets. A semantic layer is not only a technical solution, but also a strategic one. It enables organizations to align their data with their business goals, to democratize their data access and usage, and to leverage their data as a competitive advantage. A semantic layer is the key to unlocking the full potential of data and transforming it into a valuable asset.