The scandal surrounding the data analysisCompany Cambridge Analytica drew wide circles at the time. But what exactly does a data scientist do and how do you become one?
- Data analysis can do a lot of good
- Data science: attempting a definition
- The Sexiest Job of the 21st Century?
- What skills are needed as a data scientist?
- What are the areas of responsibility of a data analyst
- What role do data scientists play in companies?
- Like a forensic at CSI
- Intelligently linking data
- Trainings to the Data Scientist
- Why is a data scientist so important?
- Conclusion: Data Scientist - A profession with great future prospects
- Top books on the subject
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Data analysis can do a lot of good
Around it clear To say in advance: The scandalous revelations about Cambridge Analytica, in which its former Director of Research Christopher Wylie was significantly involved, unfortunately bring an exciting and important professional field into disrepute. Because collecting data today is a necessary and out of the modern Economy task that can no longer be ignored.
And a lot of good things can also happen with it – just think, for example, of the analysis of traffic data, which allows us to regulate traffic flows much better. Or to help patients in a much more targeted manner with health data. Without data it would not be possible at all, sophisticated Problems to solve.
The books on the subject (advertising)
Data Science is a fast growing area in today's Welt of Big Data and Technology plays a crucial role. With the proliferation of data-driven decision making across all industries, the demand for skilled data scientists has increased exponentially. But despite its growing popularity, the Term “Data science” is still vaguely understood by many.
In essence, data science refers to the process of extracting meaningful insights from large and complex data sets using statistical and computational techniques. A data scientist uses a Combination of computer science, mathematics and domain knowledge skills to collect, analyze and interpret data to solve complex problems and make informed decisions. The components of data science include data collection, data cleansing, data analysis, and data visualization.
The Sexiest Job of the 21st Century?
It is no coincidence that the job of data scientist is from Harvard Business Review authors Thomas H. Davenport and DJ Patil called it "The Sexiest Job of the 21st Century." Nevertheless, you have to be aware that this job involves a lot of responsibility in dealing with the data Background requires.
Because it is important that sensitive data is handled responsibly. And this is where a well-founded one helps Vocational Training. The former director of research at Cambridge Analytica and later whistleblower Christopher Wylie, for example, as the son of two physicists, taught himself to program after dropping out of school and went to his job at Cambridge Analytica with virtually no formal training qualification came.
What skills are needed as a data scientist?
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The role of a data analyst is multifaceted and can vary depending on the company they work for. A data analyst's primary responsibilities include collecting and organizing large data sets, cleaning and validating data, spotting patterns and trends, creating reports and visualizations, and making data-backed recommendations to key stakeholders. Data analysts may also be involved in designing and implementing new data collection methods, running experiments, and developing predictive models.
I studied computer science myself, but my job today is more of a mix of mathematician, computer scientist, statistician, softwareDeveloper and Business Process Development Manager, coupled with a good dose of common sense. But of course, my training only laid the foundation. In the course of my work, I have acquired this knowledge of the challenges that companies face today in relation to large amounts of data and also faced them years ago.
What are the areas of responsibility of a data analyst
But what does an expert, who is located between big data, analytics and business intelligence, do in his daily work? And what skills should he bring with him? And what skills should the ideal data scientist in programmatic bring to soft as well as hard skills?
With the wealth of data available, organizations are looking for ways to analyze it and use it effectively. This is where the field of data science comes in. Data science is an interdisciplinary field that involves the use of statistical and computational Methods includes to gain insights and knowledge from data. It comprises a set of techniques used to examine, analyze and make predictions from data. The Objective data science is about generating valuable insights that can be used to improve business decisions, streamline processes and drive innovation.
Data science is an essential element for all stages of the programmatic process. Built on user data and user habits, the ecosystem of digital advertising forms both a challenging and stimulating application area for all data scientists who want to work on innovative and influential problems.
What role do data scientists play in companies?
Therefore, data scientists have an important role to play in companies, because in today's data-driven world, companies rely heavily on the insights and recommendations of experts in the field. These professionals play a critical role in helping organizations make informed decisions, improve processes, and stay ahead of the competition. The Tasks However, a data analyst's skills go beyond simply calculating numbers and creating reports. They must have unique skills and expertise to extract meaningful insights from complex data sets and effectively communicate their findings to stakeholders.
The role of a data analyst requires a deep understanding of statistical analysis, data visualization, and data modeling. You must be proficient in programming languages such as Python, R, and SQL, and have an advanced knowledge of data analysis tools such as Tableau and Power BI. You must also have strong critical thinking skills and be able to Pattern and identify trends in data that can lead to actionable insights. But being a data analyst isn't just about technical skills. You must also have excellent communication skills and be able to explain complex data in simple terms to non-technical stakeholders.
Like a forensic at CSI
Basically, my job, which is still young, is about generating precisely the information that the company needs from the rapidly growing mountains of data (big data) in order to work more efficiently. The aim is to use the existing amounts of data useful to use instead of hoarding them in data stores.
My work and also my discussions with clients are sometimes reminiscent of a forensic scientist from the television series CSI. This finds the culprit by analyzing and combining the smallest of clues. In companies, the main concern is to use intelligent combination of data to both identify potential for improvement and, to a certain extent, to reliably enter the data Future to look.
Intelligently linking data
Predictions do not come from the gut, but are based on the latest findings and methods of Predictive Analysis.
One of my stated goals is not only to impart the know-how, but also to have the right tools to do this Job professionally and which make my work easier. This zest for action also benefits other companies by showing them how they can use the existing tools, such as enterprise searchSolutions, intelligently link their data. With the result of obtaining a comprehensive overall view of the topics queried in search queries.
Trainings to the Data Scientist
I still remember the times when I watched my brother transfer data with acoustic couplers or I tried it myself a few years later with my 28,8K modem and finally with a sensational 56k modem Internet to come – today unthinkable.
“Today there are only a few training opportunities like a Course at the Fraunhofer Institute or one Data Science course at DataScientest. A good basis is training in computer science, statistics, business informatics or mathematics and a high degree of social skills Expertise. In this profession, it is important to think in an interdisciplinary manner in order to link the requirements of the individual departments correctly and to identify exactly those points from the overall picture that should be further developed to the advantage of the company.
Why is a data scientist so important?
Of course I also had a personal one Motivationto take this job: I found not only Mr. Spock and Spaceship Enterprise “fascinating” at a young age, but also mathematics and of course computers.
But the job today has little to do with children's games: A data scientist must identify 100 percent with the company, because he also bears a great deal of responsibility in terms of the sustainable and responsible handling of data. Regardless of the size or the Industry, the volume of data is constantly increasing and it is becoming increasingly difficult to maintain an overview and use the insights to the advantage of the company. This is precisely why the data scientist is so important.
Conclusion: Data Scientist - A profession with great future prospects
In summary, the role of a data scientist is becoming increasingly important in today's data-driven world. These professionals have the skills and knowledge necessary to collect, analyze and interpret data to enable businesses to make informed decisions and stay ahead of the competition.
With the growing demand for data analytics in virtually every industry, the role of data scientist offers numerous opportunities for growth and advancement. Therefore, individuals interested in this field should consider developing their skills and pursuing a career in this exciting and rewarding field.
Top books on the subject
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