Systems | Development | Analytics | API | Testing

How a Tour Operation Company Used Data to Improve Their Customer Experience

The customer journey is the decision-making process each buyer goes through before converting to a paying customer of your business. Mastering this journey will require an in-depth understanding of each stage and how you can continually improve your efforts. To understand this journey, you need to take a customer-centric approach, putting yourself in your customer’s shoes to understand their point of view.

Demystifying Modern Data Platforms

July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms.

Why is Customer Feedback so Important for the FinTech Industry?

Some time ago, we covered the key metrics that a Product Manager in a fintech organization should make a top priority when determining their KPIs, breaking them down into five groups: Session-based data, Customer Feedback, Technical Metrics, Action Stats, and Revenue. With that in mind, we conducted a series of surveys on LinkedIn, asking PMs in the fintech industry which of those groups were the most important for them while running digital product analytics.

Why is Data Integration Important in a Data Management Process?

Our five key points: Your data management processes are only as effective as the quality of the data you collate. Gaining access to as much data as possible is vital if you want the business-critical insights that can set you apart from the crowd. For Ecommerce businesses, so many of the resources you use are online, such as cloud-based SaaS, ERPs, or CRMs. Integrate.io explains why data integration is such a big part of data management for Ecommerce and the benefits of an intuitive ETL and ELT tool.

Get to anomaly detection faster with Cloudera's Applied Machine Learning Prototypes

The Applied Machine Learning Prototype (AMP) for anomaly detection reduces implementation time by providing a reference model that you can build from. Built by Fast Forward Labs, and tested on AMD EYPC™ CPUs with Dell Technologies, this AMP enables data scientists across industries to truly practice predictive maintenance.