The data has become a kind of monster in many companies that is difficult to manage. PUE aims to accompany companies in this data management, betting on being close to their customers. He also specializes in cloud and DevOps models. We spoke with Enrique Martín, SE Director of the company about the perspectives and strategies of the companies.

Interview with Enrique Martín, SE Director of PUE

After 15 years at Oracle, what prompted you to join PUE?PUE seemed to me a company that attracted me professionally due to the challenges of the data sector. At a time when data has become so important for companies, PUE’s way of working, its value proposition and its experience in the sector were decisive for me to join the project. It is very satisfying to accompany all types of organizations to make good use of data to reinforce their growth and leadership.What do you consider to be the great differential value of the company?Our main value proposition is the support we offer throughout the data cycle in our three business pillars: Data, Cloud and DevOps, both on-premise, as well as in ‘cloud’ and hybrid environments. We don’t like to think in collaborating in a timely manner or in responding to a single need. We strive to always prolong the relationship with our clients by proposing improvements, making the service evolve, materializing new use cases, finding new formulas so that they can save on costs… In addition, our team is 100% certified in the technologies that we implement and constantly training, a guarantee of quality when carrying out all the projects, since the workers know the latest trends in the sector and apply the one that best suits each case.What trends will predominate in data management in companies this 2023? what are the next challenges?Data has become the main protagonist in the digital transformation processes of successful companies, and the main catalyst for their growth. For this reason, the main challenge is to see how companies are capable of extracting value from data. From a technological point of view, there are 3 clear challenges: improving data governance, evolving towards an agile organizational model based on data domains ( Data Mesh) and architecture optimization (Lakehouses).What is the most innovative in current cloud strategies?Over the last few years we have seen how many organizations have joined the digitization bandwagon. This has accelerated the number of projects based on migration to the cloud, but not all of them have been successful from the point of view of optimization (above all, costs) or innovation. Therefore, the great challenge in this phase of maturity is to improve efficiency, perhaps with hybrid or multicloud approaches. This is even more important when we focus on the world of data, with the additional governance problems that it can bring. As I said, data governance and the Data Mesh orientation are aimed at making our infrastructure efficient with a view to truly turning it into a competitive key that allows us to optimize processes, generate new lines of business and use cases, sharpen automation and execute a cost reduction.Many organizations are betting on a return to on-premise. What is this type of strategy for?Although it is true that for many companies migration to the cloud meant improvements in terms of accessibility, storage, scalability and flexibility of the data, betting on the ‘cloud’ does not necessarily have to bring these benefits in all cases. Our recommendation is always that we start any type of project is to carry out a prior evaluation to find out what situation each company is going through and what needs it has to evaluate whether it is interesting to implement a project in the cloud or not. Since it is not always necessary to take the step of migrating. For some companies, their workloads can work perfectly on-premises while making the most of the data. However, the ‘cloud’ will continue to be very important in data management strategies.They have recently published a study on the state of the AA.PP. on the cloud. What kind of advantages does cloud migration bring to public institutions?Public Administrations have realized the possibilities they have to improve their work if they get all the value out of the large amount of data they store. There is a study that reflects that one in five Spanish administrations has a hybrid cloud and that more than half of the entities have already made some kind of jump to the cloud. Among the benefits that cloud models bring to AA.PP., the efficiency and reduction of infrastructure costs (58.7%), the reduction of operating costs (54%) and the quality of service (54%) stand out. In addition, these entities are not only realizing the power of data, but are also aware of the importance of data governance. In fact, 39% have decided to implement a data governance transformation program.Technology companies are going through a turbulent moment in terms of retaining internal talent. How are you living in PUE?For us, human talent represents the core of our value proposition in all the projects in which we participate. Despite the moment the sector is going through, we are committed to the continuous training of talent from the first day they join our team. For example, we have just incorporated 17 people who have participated in the Data Sentinels project, our training initiative and official certification with contracting commitment. Our ambition is for them to grow with us and apply all the knowledge they have obtained. We have 160 highly qualified professionals certified in the main technologies on the market. A guarantee guarantee of our work for any type of project that supports that all of us who form PUE have a very deep technical and theoretical knowledge.How do you think generative AI will affect data strategies in companies?Generative AI is going to influence our lives through various points. Not only the arrival of Chat GPT has revolutionized the way in which we communicate with a machine or search for information. In the data analytics industry, Artificial Intelligence has been used for many years to perform predictive analysis, create early response models by combining it with Machine Learning and optimize decision making in companies. I don’t think we have to see it as a threat , but as an aid that will promote the digitization of services and, specifically, the management and exploitation of data. Companies will create their own generative AI models with the information they have to simplify and improve interaction with customers.