Friday, March 24

The 5 trends of the Data sector for 2023

Data 2023

At a time when the volume of data does not stop growing, it is crucial that companies have an effective data strategy, capable of unlocking the value of their information and boosting their productivity and innovation.

From Bluetab they have presented the trends in this sector that will impact Spanish companies during 2023. This area is, without a doubt, one of the most powerful technological trends of the moment for all types of companies, and it is revolutionizing companies around the world.

5 data trends

The five trends in the sector for this year are the following:

  • Data Warehouses will continue to grow in the Cloud. In the last year there has been a phenomenon that has caught the attention of data experts: the remarkable growth of Data Warehouses in the Cloud. In fact, in a 2022 report, Gartner predicted that by 2024, 75% of data workloads will be in the Cloud. From Bluetab they have already warned how this prediction is becoming a reality for all the sectors in which their clients operate, among which are financial services, media, telecommunications, insurance, utilities, industry or public administration. The reasons for this trend are the benefits of hosting data in the cloud, such as the possibility of processing data in real time or memory to reduce latency times, in addition to the inherent benefits of the cloud: scalability, flexibility, cost reduction …
  • Machine Learning will remain one of the big trends in data. Very notable advances are being made in Machine Learning models that have to do with language. An example is the now very popular ChatGPT, which, like other Large Language Models (LLM), is capable of learning in order to subsequently apply the knowledge acquired to other types of tasks. As a consequence of these advances, Bluetab anticipates that the use cases based on LLMs will have a strong development. Data management is being transformed so that machine learning can be applied in production and at scale. In order to apply it, the data structures must undergo a transformation similar to that which occurred in Business Intelligence (BI) matters. In this way, Machine Learning models can be trained more efficiently. On the other hand, this transformation will make it possible to automate and industrialize the training and production of Machine Learning models through data processes (pipelines).
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These are the 5 trends in the Data sector for 2023

  • The data will be a transversal axis to promote data-driven companies. There are more and more companies that want to be data-driven, that is, they want to implement strategies and decisions based on reproducible data that can be shared within the company at all levels. That is why the need to produce data applications is increasing. This pressure will lead to the modernization of Business Intelligence data stacks, data analysis applications and even the profile of business data analysts. These will go from being mere analytical users who consume information and interpret it, to being analytical users capable of producing and sharing their own applications with the entire organization. Reaching the goal of being data-driven will not only allow companies to improve decision-making and accelerate their productivity, but it will also become a key factor in determining their digital success. In this sense, a Gartner report indicates that by 2025, 80% of organizations that want to scale their digital businesses will fail for not having adopted a modern approach to data governance and analytics.
  • Training in Data Science, a key discipline for companies. As the investment in data continues to grow, the need for qualified people capable of managing and working with data science increases. IBM predicted that there would be 2,720,000 job openings for data scientists in 2020, but after the Covid-19 pandemic, the shortage of professionals became even more evident. In this regard, training by companies is key. Currently, several companies are implementing programs to train university students in Data Science and prepare them for the world of work. Bluetab, for example, has been carrying out the Talent Data Path program for several years, in which they hire from the beginning and train recent graduates and professionals from other specialties at a high level in data technology, who go through a mentoring process to training at a high level in the world of data.
  • Data Governance goes from being a “nice-to-have” to being a “must have”. Data Governance has grown substantially in the last three years, also driven by European initiatives such as Gaia-X. During this time, Bluetab has identified a notable growth both in the projects related to this discipline and in the demands for the use of said systems. However, although some large companies are already putting data governance into practice, there are still immature and incipient environments in the business fabric. Now, Data Governance has become imperative in order to grow and scale. In this time, we have also seen how terms such as ‘data mesh’, ‘data products’ or ‘data observability’ have become popular, which, in reality, always point to the same primary objective: solving the problem of trust and availability of the data. For this, Data Governance is postulated as an umbrella to address this complex issue, where various issues come into play, such as: having the data and identifying it (data catalog or data glossary), knowing where it comes from (data lineage) or having confidence in that they are complete and correct (data quality).
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