Tripfez & Salam Standard use big data analytics to provide Muslims a blessed travel experience

In a market saturated with international players all offering variations of the same travel booking products, this Malaysian online travel trailblazer harnessed big data analytics (BDA) to stand out above the rest, aggregating millions of search results through their service.



Through Tripfez and Salam Standard, thousands of users request thousands of hotels, millions of reviews and photos. Tripfez focuses on the speed of processing to create a great consumer experience. At the same time, a lot of emphases are put into understanding user behaviour which is at the core of the entire operation to further increase conversion and improving consumer experience. Salam Standard not only focuses on speed, but a lot of emphases are put on processing millions of requests and data sets every minute, and transforming them. The end result are an analysis of data that will reveal data pattern, including data that shows top destinations, top selected hotels from more than 300,000 hotels worldwide across 35,000 cities.

In both cases, BDA has allowed Tripfez and Salam Standard not only the ability to process millions of datasets, but ultimately to stay ahead of its competitors, through the ability to process vast amounts of real-time data fast and efficiently, and by enabling its analysis team to better understand and predict user patterns on the website as well as user booking patterns.


The tourism industry is highly volatile, where booking trends for certain destinations can change in a heartbeat.  A whole target group can change their preference and purchasing behaviour overnight.  Furthermore, processing of all relevant data was a resource-intensive and expensive process for the company. Tripfez has placed great importance in its ability to process millions of datasets in real-time and without downtime to ensure a smooth customer experience while great emphasis was put by Salam Standard on the ability to process millions of datasets every second in order to understand user specific booking patterns and predict future trends.

The company’s team of analysts must be able to process vast amount of data efficiently as a guide to future marketing decisions as well as trends and booking patterns that will help other travel platforms to better understand customer’s behaviour. It was also important to ensure that any advanced data analytics exercise is not just a mere business intelligence process with a cool dashboard. It is about extracting valuable insights from data and empowering decision makers with analytics that allows them to make strategic decisions and ultimately enable a data-driven organization.



Tripfez and Salam Standard currently store more than 20TB of data on Hadoop with a projection to increase to 100TB in the next 5 years.  The company uses Hadoop to store and process web log data; Hive to query and aggregate the data into tables; SQL Server for reporting against aggregated data; and JMP, a visual discovery software from SAS to further explore the aggregated data.

Hadoop is an open source software project that enables distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with very high degree of fault tolerance. Rather than relying on high-end hardware, the resiliency of these clusters comes from the software’s ability to detect and handle failures at the application layer.

Business Benefits

A big benefit of BDA is the delivery of timely insights from the vast amount of data. This includes those already stored in the company databases, from external third-party sources, the Internet and social media. As a result, this allows real-time monitoring and forecasting events that impact business performance and operations. Such understanding and predictive abilities allow much quicker response to market changes and supports both Tripfez and Salam Standard to stay on top of these changes rather than being surprised by them. It changes the business position from being reactive towards a more proactive stance at the same time enable other travel platforms to leverage on users booking patterns to improve their conversion.


With the implementation of BDA practices, the hardware infrastructure for data processing can be reduced and the speed significantly increased.  BDA also allows Tripfez and Salam Standard to scale the analysis of the vast amount of data and maintain data ingestion without congesting or crashing the entire system. A substantial amount of cost-savings can be brought about for the company.

Overall, Tripfez’s and Salam Standard’s use of BDA helps it to stay ahead of its competitors, not only through the ability to process vast amount of real-time data fast and efficiently, but also to enable its team to better analyse the patterns of users. BDA also supports the company in processing years of historical data, providing its marketing team with the ability to follow user behaviour trends. This allows the team to strategize and to improve its customer experience better than other players.

The Future

From data centres to software architecture, scalability is at the heart of Tripfez and Salam Standard on many levels. Moving forward, BDA will play a big role in all of Tripfez and Salam Standard decision making processes to create a data driven decision enterprise, and at the same time ensuring that user experience is at the core of all decisions.

Doing business now and in the future means harnessing the explosive growth of data. The mobile data generation, real-time connectivity and digital businesses have changed the nature of the game when it comes to protecting data assets. As a result, BDA has an increasingly important role to play in data security, which the company wants to intensify in the future. It also wants to use BDA to transform intrusion detection, differential privacy and malware countermeasures.

Note: This is an updated case study of the previous Lagisatu story, which has since pivoted to Tripfez and Salam Standard.


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