Delivering premium traveler experiences while optimizing operations are dueling challenges for the Travel & Hospitality industry. Faced with tight IT budgets, rising customer expectations and an increasingly digital workforce, it’s a time of rapid technological transformation for the industry.
To remain competitive, keeping up with high velocity software releases is critical, and so is ensuring the data lifecycle processes keep pace and that the benefits of DevOps practices extend to data environments. Stelligent combines deep Travel & Hospitality domain expertise with technology leadership and unique digital transformation experience.
Having adapted our proven ‘automate everything’ approach for use throughout the Travel & Hospitality data lifecycle, Stelligent can automate your organization’s data events and integrate with Continuous Delivery pipelines to extract value from your data and deliver these benefits:
Faster Cycle Time
Reuse of database and transformation code, continuous integration between applications and data, and faster feedback for development teams all reduce data development time.
Increase Innovation
Focus your development efforts on solutions and products that extract value from your data. Faster cycle times allow for experimentation and iteration on data transformations, reporting, and machine learning models.
Improve Data Quality
Test driven development and automated quality controls ensure that the integrity of your data is high from creation, through transformation, and into value extraction.
Scalability and Reliability
Automated infrastructure allows your environment to adapt on-demand to sizing and capacity requirements. Codifying infrastructure improves reliability and allows iteration and continuous improvement of the data systems. Continuous monitoring provides feedback to systems operations teams.
Lower Costs
Reducing manual tasks increases development capacity and reduces errors in the data lifecycle.
Unlock the value of your data faster
Stelligent DataOps services can leverage automation and promote collaboration among your data scientists, engineers, and other technologists to dramatically speed the time-to-value of your data.