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10 training demands to tackle digital transformation
Digital transformationis the change associated with the application of digital technology in all aspects of human society.
Due to market transformations, such as the appearance of new competitors, the omnichannel of consumption habits and the influence on social networks, companies need to take a more adjusted approach to reality and compete in this new environment of digital change.
A Spanish training center, MBIT School, dedicated exclusively to Business Intelligence and Big Data, has analyzed which are the competences and matters most demanded by companies that want to have a trained and expert staff to address the disruption imposed by the market. The competences and matters most in demand are:
1. Big Data Architectures: the designers have to know the technical architecture that supports the new processes and applications to have a vision of the whole and the industry, at the same time that they have the adequate criteria to solve the analytical problems and offer the services That are required.
2. Big Data for Managers: companies request this training with the aim of providing managers with the necessary knowledge to handle the possibilities of Big Data in the different processes of the company, to know the new roles that they must incorporate in their organizations or propose and devise certain projects related to digital transformation.
3. Big Data project management: the objective of the project managers with this training is to work in a known territory, in order to reduce the failure rate of the newly created Big data projects, avoid known errors and incorporate methodologies Agile in management.
4. Data storage and query in Big Data environments: professionals need to be aware of the possibilities offered by the new generation of database systems, called NoSQL, to have a new perspective of the possibilities at their disposal and provide a vision of the strengths and weaknesses of each and the criteria to select the most appropriate depending on the objective of the project.
5. Deep Learning: companies seek to train their workers to build solutions in the analysis of real-time images, voice or detection of threats, through deep learning algorithms, which are at the base of artificial intelligence applications.
6. Machine Learning: the objective of companies with this training is to act as a catalyst for the development and adoption of the application of learning algorithms to create programs, identify patterns or make predictions or recommendations.
7. Data Science with Python: data scientists aim to work with tools implemented in large companies, such as Google, YouTube or Facebook, that provide simplicity, multiplatform and the possibility of being used by various programming styles, such as the tool Python.
8. Data Science with R: the company seeks to assign the analyst with a complete training on a daily work tool, the R language, provides a huge range of statistical tools and graphics.
9. Visualization tools: Data scientists must have an accelerated knowledge of the latest trends in visualization techniques with the latest tools both open source and commercial with Visual Analytics.
10. Agile methodologies: companies work to achieve a minimum competitive advantage when putting products on the market in record time. With agile methodologies, such as SCRUM, the user is allowed to be part of decision making and prioritization of results, allowing the product to adapt to the real needs of the client.
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