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Trio Data Engine

Preparing data for downstream analytics

The perfect processing data hub for high volume XML/JSON - taking XML data from multiple sources, and preparing it for downstream analysis by multiple BI applications

Data Challenges

  • Enterprise applications generate big data
  • Created and stored on variety of system/formats
  • Transaction data (request/reply) often in XML/JSON
  • Raw data needs careful cleansing, matching and processing
  • Data complexity and scale make analysis difficult
  • Challenges in getting prepared data in a timely manner
  • Struggle with analytic processes that don’t yield the insights needed
trio data engine data challenge
trio data engine solution

Trio Solution

  • Agnostic way of collecting, preparing and aggregating API transaction data for downstream advanced analytics
  • Pushes XML data in right formats into other BI platforms
  • Ability to take complex data and transform it for analysis speedily and at scale
  • Expertise in scalable API monitoring and XML/JSON analytics
  • Ability to take data from a variety of sources (IBE, CRS or PSS)
  • Platform for collecting, normalising and preparing data
  • Ability to aggregate large data volumes for analysis
trio data engine data challenge

Data Challenges

  • Enterprise applications generate big data
  • Created and stored on variety of system/formats
  • Transaction data (request/reply) often in XML/JSON
  • Raw data needs careful cleansing, matching and processing
  • Data complexity and scale make analysis difficult
  • Challenges in getting prepared data in a timely manner
  • Struggle with analytic processes that don’t yield the insights needed
trio data engine solution

Trio Solution

  • Agnostic way of collecting, preparing and aggregating API transaction data for downstream advanced analytics
  • Pushes XML data in right formats into other BI platforms
  • Ability to take complex data and transform it for analysis speedily and at scale
  • Expertise in scalable API monitoring and XML/JSON analytics
  • Ability to take data from a variety of sources (IBE, CRS or PSS)
  • Platform for collecting, normalising and preparing data
  • Ability to aggregate large data volumes for analysis
Benefits
  • Well prepared data for analysis maximises its intelligence potential
  •  Getting large-scale XML data fit for analysis and enterprise-wide sharing
  • Reduces time and complexity of preparing raw XML for BI analysis
  • Delivering complete and consistent data to ensure accuracy for analysis
  • Versatile and highly scalable platform to accommodate growth
  • Helping to leverage the rich insights embedded in complex XML data
How Trio Data Engine Works

Trio Data Engine acts as a processing hub for a variety of functions such as cleansing, extraction, translation, aggregation, retention and analysis. The prepared data can then be fed into a variety of other BI systems for further analysis and consumer presentation to extract insights for business. Alternatively, the Trio Engine’s own analytics and presentation layer can be used for this purpose.

Trio Data Engine how it works diagram
The Processes
Collection
Collection

The Trio Engine captures the raw data (unobtrusively and without impact on servers or networks) from cloud or on premise sources including networks, cloud based object stores or big data message queues.

Cleansing
Cleansing

Data cleansing involves identifying and correcting messy, raw data, such as errors and anomalies. Taken from disparate sources, the data is cleansed and put into a consistent unified format to adhere to defined schemas

Extraction
Extraction

Using business rules or look-up tables, the data is extracted and blended from different data sources into a homogenous format. Transactional data is merged with static data that defines products, clients and other business entities

Translation
Translation

Our experts in travel data work with your team to define the optimised and meaningful meta data descriptions and data relationships that give you the right data you need for further analysis. Data can be enriched  to produce additional data sets that make it easier for your downstream processes.

Aggregation
Aggregation

Big data is expressed in a summary form. With large volumes of raw transactions,  reporting is based on aggregated information. Getting aggregation and data enrichments right can generate significant performance benefits, with inherent improvements in analysis and reporting capabilities.

Retention
Retention

Trio Data Engine pushes data to decision making systems, but can manage some retention as needed. If the output system is focused on dynamic pricing, its ability to store large scale search data is limited but the output might benefit from storing some trend metrics such as monthly averages or gradients.

Interested in finding out more?
Resources
Kafka APIs Blog

Taking Kafka to the Next Level for APIs Blog

Trio Data Engine Data Sheet

ELK Stack Blog

Feeding your ELK Stack Blog

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