The purpose of this unit is to provide you with a contextualization of the importance of the human resources department in organizations and how its study favors the inter-labor relations of workers and the functioning of the company. Likewise, you will learn the basic concepts, and their fundamentals based on theory, which will allow you to lay the foundations of your learning about the complexity of the processes related to the human resources department.

1. How to successfully get into data
science
In the midst of the technological boom, big data is no longer just a trend, but
has become an important pillar in the emergence of new professions. The
ability to analyze, manage and use large amounts of data has become
important in all industries.
From healthcare, where big data analytics helps in early disease detection, to
marketing, where they enable detailed and personalized campaigns, big data is
revolutionizing the way we work. New careers such as data scientist, data
engineer and business analyst are at the forefront, decoding information to
make accurate decisions
Artificial intelligence is also driven by Big Data, creating jobs in areas such as
algorithm development and interpretation of results. Our knowledge is the
most valuable asset of our time, and mastering its management is a crucial
skill we must acquire. The emergence of new professions, driven by Big
Data, not only represents the current era, but also shapes our work and

2. technological advances. The engine is undoubtedly responsible for a
professional revolution never seen before.
The concept of Big Data is broad and diverse and can be addressed through
various means. From my point of view, computing is the most appropriate
reference point to measure it. The use of computers in an office is common
among professionals. The software engineer does not need as much
knowledge in the field as the professional who uses office platforms or
email, since computing is a tool that could be used without it.
While big data is similar to computing in many ways, it also affects
professionals with advanced technical skills and can affect any aspect of a
company's governance.
Learning some aspects or others is necessary to maximize the potential of
big data, depending on our professional career and the objectives we
pursue. However, there are some things that every professional should take
into account: knowledge of the main ecosystems (Azure, AWS and Google
Cloud), specific visualization tools (Tableau or Power BI), an analytical and
statistical-based system, as well as visualization of databases, both
structured and unstructured. Of course, experience in the field.'"
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3. Data science exists in the context of a highly information-driven world.
Crucial participants involved in identifying, apprehending and emphasizing to the maximum.
Important. Data professionals should be excited about continuous learning and.
In addition to basic training in computing, mathematics or exploration.
Statistical data. However, it is not only necessary to have degrees and experience in
programming languages.
The use of R and Python is essential.
A comprehensive understanding of statistics is necessary, beyond the level of formal
education.'"
Implement data analysis techniques... They must make the most of them.’ The.
Online learning platforms and other resources that can improve skills.
Using techniques requires a self-taught mentality. Become like. TO.
Data expertise required persistent effort and dedication, which led to a significant increase in
profits.
The BRICS are an invaluable source of opportunities.