In this context, the characterization of samples based on several analytical setups is now recognized as an efficient strategy to improve the coverage of metabolic complexity. In addition, despite major technological advances, it remains challenging to measure all the compounds defining the metabolic network of a biological system. However, collecting specimens in this setting can be difficult to standardize, especially when groups of patients with different degrees of disease severity are considered. 6Toxalim, Research Centre in Food Toxicology, Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, Franceīecause of its ability to generate biological hypotheses, metabolomics offers an innovative and promising approach in many fields, including clinical research.5Service of Nephrology and Hypertension, Department of Medicine, Geneva University Hospitals (HUG), Geneva, Switzerland.4Unité Statistique, Sensométrie et Chimiométrie, Nantes, France.3Translational Biomarker Group, Department of Internal Medicine Specialties, University of Geneva, Geneva, Switzerland.2Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.1School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.There’s also a linear aspect to these terms that differentiates them.Julien Boccard 1,2*, Domitille Schvartz 3, Santiago Codesido 1,2, Mohamed Hanafi 4, Yoric Gagnebin 1,2, Belén Ponte 5, Fabien Jourdan 6 and Serge Rudaz 1,2 The differences become clear when we crystalize the definitions:Īnalytics = organizing and examining data. This can have a thrilling, “aha moment” aspect to it. In the context of data and analytics, the word insight refers to an analyst or business user discovering a pattern in data or a relationship between variables that they didn’t previously know existed. The broad definition of insight is a deep understanding of a situation (or person or thing).

In this way, users not only answer the specific questions they started with but they discover new questions to ask. The best data analytics tools enable users to freely explore big datasets that combine relevant data from multiple sources. The goal of analytics is to answer specific questions, discover new insights, and help organizations make better, data-driven decisions. What is Analytics?Īnalytics is the use of tools and processes to combine and examine sets of data to identify patterns, relationships and trends. For data analysis to take place, this raw data must be transformed into clean, business ready information through a process known as data integration. Given how much of our lives happens digitally today, organizations have an abundance of raw data on hand. Raw data, also known as source data or primary data, is facts and figures in the original form and organization that they were collected from the source. These facts can be in the form of numbers, symbols or words and are typically stored digitally.

Simply put, data is a collection of facts, representing measurements or descriptions of a specific situation.

Here we define the terms data, analytics, and insights and examine the differences between them.

Gaining insights