What is ROLAP?

ROLAP systems operate by using relational tables in a data warehouse to store data rather than relying on multidimensional data models or OLAP cubes. When users submit ad-hoc user requests for analysis, ROLAP systems process these through SQL queries, enabling them to pull insights directly from relational databases. This dynamic querying approach eliminates the need for pre-aggregated data, saving storage space and making it easier to manage large datasets.

ROLAP systems typically rely on an OLAP server as a middle layer between the user interface (front-end) and the data sources. This ensures that data is presented in a user-friendly format while maintaining the optimization needed to handle complex queries across relational tables.

ROLAP differs from multidimensional online analytical processing (MOLAP) in its reliance on relational databases rather than multidimensional databases or data cubes. While MOLAP provides faster query responses due to pre-aggregated data, ROLAP offers greater scalability and the ability to handle dynamic, real-time queries.

A hybrid approach, known as hybrid OLAP (HOLAP), combines the strengths of ROLAP and MOLAP by utilizing pre-aggregated multidimensional analysis for frequent queries while relying on ROLAP for ad-hoc analysis of large amounts of data.

Phocas employs relational OLAP principles to empower businesses with robust data analysis capabilities that suit a variety of needs, from financial planning to business intelligence. Here are three ways Phocas excels in leveraging ROLAP:

1. Seamless integration with multiple data sources

Phocas connects easily with data warehouses and relational databases, including popular RDBMS systems like SQL Server and SSAS. Its ability to integrate with various ERP systems ensures that your data sources are consolidated into a single platform. This approach eliminates the hassle of managing disparate systems and enables multidimensional analysis across your entire operation.

2. Real-time insights with ad-hoc queries

By utilizing ROLAP, Phocas enables real-time analysis of operational and financial data. Users can perform ad-hoc data analysis on relational tables without waiting for pre-calculated results, making it ideal for fast decision-making. Whether you need to drill down into multidimensional data models or create on-the-fly reports, Phocas delivers the insights you need to act quickly.

3. Scalability for growing businesses

As your business grows, so does the complexity and volume of your data. Phocas' ROLAP capabilities provide the scalability needed to handle increasing data volumes without sacrificing performance. Its optimization ensures that even as datasets expand, your analyses remain fast and reliable, saving you time and resources.

The Phocas platform is purpose-built for wholesale distribution, manufacturing, and retail industries. ROLAP is particularly valuable in these industries as fast, secure access to large datasets and consolidated data is critical for business intelligence and financial planning. For example:

• Financial forecasting: Phocas’ ROLAP-driven platform enables finance teams to build dynamic financial reports and forecasts by consolidating data from multiple data sources. You can easily track live actuals then revisit and adjust forecasts based on current trends.
• Sales performance analysis: With ROLAP, sales managers can drill down into detailed transaction-level data, identify trends, and adjust sales strategies without needing complex Excel formulas or php scripts.
• Operational efficiency: ROLAP supports ad-hoc queries, enabling managers to identify inefficiencies in supply chain by analyzing real-time data from relational databases.