Advanced telematics technologies are transforming the transportation industry.

With the emergence of IoT, sensors and mobile applications collect massive amounts of data that determine driver effectiveness, generate real-time supply and demand heat maps, optimize pricing and lead to a better decision-making process.

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Operational Efficiency

Analytics processed by an order of magnitude are optimizing the surge price, guiding drivers to locations on demand and more
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Faster Time to Market

Developing new services in less time and at a fraction of the cost
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Reduced TCO

Eliminating the need to deploy and maintain additional data stores and data copies, resulting in substantial cost reduction

Case Study – Ride Sharing

iguazio was approached by a leading ride-hailing company to build their next generation data lake. The Uber-like international company offers transportation services to millions of passengers across multiple countries. Up until today, they have used AWS data services, but their substantial expansion and growing demand for real-time insights have led them to seek a platform that better supports scalability, strict security requirements and overall performance.

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The Challenge

Prior to iguazio, the customer used a solution that was based on Amazon Data Services and Amazon EC2. The data pipeline was complex, it didn’t scale well and couldn’t address the company’s performance and security requirements. The company’s mobile app sent passenger and driver data to the following services/databases: MySQL – storing raw data, Kinesis – streaming data and Redis – storing real-time information for quick access. Data was then pushed to Amazon S3 once a day and from there to Amazon Redshift. The company performed ETL and analytics jobs in Redshift to generate reports while providing access to various consumers, including data science teams. This method performed poorly and had scalability issues once Redshift exceeded 15 concurrent sessions. Furthermore, the need to use many data services added additional overhead to the data management platform and influenced the time it took to develop new services and applications. The key challenge was to eliminate tedious IT plumbing tasks so that data engineers could focus on developing new services. The company was experiencing extremely fast growth and was therefore looking for ways to build an optimized and efficient data lake that can scale up with the business. Amazon Data Services can be extremely expensive and prices increase as the customer’s business grows since charging is done per specific workload.
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The Solution

The iguazio Unified Data Platform moved analytics from batch mode to real-time and helped the organization optimize its business, providing better service to customers and increasing revenue.

These real-time insights enabled a variety of new applications, such as:

  • Driver incentives to determine driver bonuses in real-time, by analyzing and increasing driver effectiveness, the number of runs during peak driving times and rider satisfaction.
  • Maximize driver profits while reducing passenger wait times by optimizing driver the decision-making process using advanced real-time supply and demand heatmaps.
  • Surge pricing optimization which correlates passenger demand data with external data sources, such as news, weather and social media.

The iguazio unified data platform enabled the client to ingest data directly to a single data store in different formats such as stream, object/file and database records. The customer could stream data directly from the application to the iguazio platform using common REST APIs (e.g. a DynamoDB and S3-like API) eliminating the need for a dedicated streaming cluster. In this simplified pipeline, the customer generated real-time analytics using Spark jobs running on top of iguazio’s NoSQL database as opposed to previous batch operation methods where the data had to go a long way till reaching its destination. Based on the analyzed data, the customer rapidly calculated the surge price, customer churn, unique bookings and more. Given that the iguazio platform supports Amazon-like APIs and is integrated with Spark, the customer didn’t even need to change the code.

iguazio provided the customer with unique value by enabling continuous analytics and event-driven applications while eliminating the complexity of it’s data pipeline. By using the iguazio Unified Data platform, the company continues to offer new innovative services at a faster time to market.