Nowadays, masses of data are collected and stored. In addition, data is becoming increasingly important for businesses in the course of the digitalization. Because in all businesses with more or less complex business processes, the accruing data volume is enormous. A powerful data science team can help to cope with the frequently existing “data jam”. By means of predictive analytics and machine learning, businesses can even gain positive insights for their respective operations. For example, connections and structures can be easily recognized and forecasts can be created by mouse click. Thus, the results pave the way for a positive economic development of the own business.
Data Science in the Course of Time
In recent years, an increasing standardization and professionalization can be seen, especially in the data science area. This is primarily due to the fact that data storage and usage is becoming increasingly important across industries in order to be able to meet the customers’ needs. However, shortened product life cycles and process optimizations, which are becoming increasingly important due to globalization, also increase businesses’ dependency on analytical insights of a data science team.
Steps to Develop and Operate a Powerful Data Science Team
First of all, it needs to be clarified whether data science competencies should be bundled in a team or whether a decentralized solution seems more sensible (i.e. a distribution of the competencies among the various departments). In this process, both solution approaches may be beneficial depending on the business’s organization. Simon Nehls will explain which approach is possible for your business in his webinar on 13 October at 11 am. In addition, learn which benefit the development of a powerful data science team offers for your organization.
Simon Nehls – Your Specialist in the Data Science Area
Simon Nehls, Consultant with b.telligent, specializes in data science, modeling and analytical decision support. He advises and coaches customers from various industries such as e.g. energy, e-commerce and telecommunication. His core topics are predictive analytics and data mining as well as organization development in the analytical environment. Due to his background in applied economy and market research, customer- and market-related thinking and recipient-focused and implementation-oriented knowledge transfer are among his strengths.
Register today for the free webinar – the number of participants is limited.
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We are looking forward to your participation!