Scalable self-service data exploration and visualisation is currently a hot topic. In two articles we explore how new and easier methods of data discovery is helping organisations on the tough journey to becoming more data-driven. This article (Part 1) gives an overview of some of the exploration techniques, while Part 2 describes (with charts) how the Trio platform can be used for a drilling deeper into search and booking data, to be able to report on the data set that is meaningful and relevant to a B2B distributor.
Data on the Rise and Making it Easier to Use
The travel business is fueled by data. The ability to translate raw data into useable insights is a must, regardless of whether you’re a large international organisation or a smaller operator. This is especially true of the vast quantities of transaction data flowing through the industry’s APIs. But to do this with success, and many enterprises today still don’t, means knowing what data and metrics are important to your business and harnessing the right tools. At one time, the power of data was mostly in the hands of a few data experts with the skills necessary to organise, crunch, and interpret the data for their organisation. But things have changed with the emergence of technologies capable of making data shareable and interpretable for non-data analysts. Today, getting access to insight means data analysis has become too important to limit its use just to the experts. Hence the self-service option is gaining momentum.
There are two schools of thought on whether self-service is a good idea or not. The sceptics, who think that data insights will be compromised with inexperience, and the enthusiasts, who are convinced that faster insights lead to better and more decisive action. Reality, as usual, lies somewhere in between. Business users want and need self-service analytics because the level of agility demanded by the competitive environment can no longer be met by a centralised approach alone.
In response, data analytic platforms such as the Trio platform are becoming easier to use. We know it’s increasingly important for business users to have easy access to the reports and insights they need to drive business. While critical and complex data-driven decisions are likely to remain the territory of data experts, self-service data analytics is helping professionals across departments get the right insights faster and under their own steam. Armed with early insights they make better operational decisions, especially in situations dependent on real-time data. From contracting to distribution, from sales and marketing to revenue management, users from a variety of disciplines are increasingly able to explore API data, without being experts, or relying on a BI or IT team.
Self-Service and Assisted Data Exploration
The best tools don’t just help visualise data, they interact with users as they perform data exploration. Instead of just spitting out limited reports, the best data exploration tools now interact with the user to help him or her drill down deeper into datasets and even make recommendations for visualisations, and even automate the exploration process through machine-learning.
Data analysis and visualisation platforms are getting more user-friendly and easy to use, even to the point of offering question and answer style guidance and potential scenarios along the way. This is the approach that Triometric has taken with the latest version of its analytics platform. The goal is to broaden the reach of data, by removing barriers to access and understanding.
Concepts in Data
When a user builds a report on virtually any topic that report will consist of what are usually referred to as measurements and dimensions. Keeping it simple, the measurements are typically the columnar data values that get added up or averaged whilst the dimensions are the rows in the report which are used to create subtotals. For example a hotel distribution manager might construct a simple report which shows the number of searches and bookings by hotel property. The number of searches and bookings are the measurements whilst the hotel property and check-in date are the dimensions.
Part 2 describes (with charts) how the Trio platform can be used for a drilling deeper into search and booking data, to be able to report on the data set that is meaningful and relevant to a B2B distributor.
Trio is a scalable XML/JSON analytics platform (on-premise and cloud) that can be readily deployed to analyse and apply API search and booking insights for a travel organisation’s distribution operation.