When I started in Clariba in 2019 as an intern wasn't expecting to be able to combine one of my hobbies, football, with my work. It was the best way to start learning new technologies and start gaining experience while growing in a personal and in a professional way.
abril 2017. During my last year of University I started in Clariba as an intern and it’s been a while since then! 4 years of multiple customers, projects, and colleagues. And, of course, some after works too!
Traditionally, the only data available to the football industry for gaining insight and analytics into a match or training session was the same data we could see on television: goals scored, corners won, ball possession, and so on. Nowadays, thanks to advanced data collection devices, tracking and cameras, real time data with X, Y, Z coordinates registering every relevant action for each player during training sessions and games is abundantly available.
As experts in data warehousing and analytics we are increasingly faced with requirements where our customers need very advanced “dashboarding”. Their requirement may include the ability to execute transactional activities such as creating a Purchase Order, triggering a data process in a back-end system or providing “always on” multimedia streaming and broadcasting at a large scale and this across multiple devices (Android, iOS, Windows, MacOS, etc).
SAP Analytics Cloud is just for Analytics. This is how we usually misunderstand the true potential of SAP Analytics Cloud. In this post, we explain key features that SAP Analytics Cloud provides for successfully planning, budgeting and analyzing data. This blog comes from our expertise working in different scenarios we have satisfactorily developed for our customers.
Some tools can be more productive than others. Throughout our experience in implementing an optimal machine-learning pipeline in production, we have learned to appreciate the raw strength of the combination of SAP HANA with SAP Data Services. The amount of time that can be saved by reformulating the approach and optimizing it to use this combination is significant, compared to a vanilla approach involving usage of Python for data wrangling, cleaning, discovery, and normalization, which are significant aspects of machine learning pipeline development.
Clariba, a leading data-driven digital transformation solutions SAP partner based in Europe and the Middle East received two highly acclaimed awards at the SAP Summit 2019 in Dubai, UAE. “We are honored to be the winner of the SAP Best Intelligent Platform Partner 2019 in the Middle East. This award showcases the strength of our innovative work for clients in partnership with SAP”, says Marc Haberland, Founder & Group CEO, Clariba. “To also receive the SAP Quality Excellence Award is a great achievement and testament to the outstanding work the entire Clariba team delivers on a daily basis to enterprise customers,” he adds.
SAP Vora is an in-memory computing solution from SAP that allows to develop analytical applications from massive data sources (Big Data) and NoSQL. In this article we will introduce you to its main components and features. Furthermore, we will disclose some initial insights about its performance by using a test case developed at Clariba. Let’s start with a brief introduction.
Helping our customers in their Digital Transformation journey requires us to constantly stay outside of our comfort zone, to make sure we are a step ahead of our competitors while adding value to our customers. Our participation in the Du Tough Mudder race, with a team led by our Global Sales Manager Luca Spinelli, reminded us of key values we try to keep always in mind in whatever we do. Read the full story written by him.