Data Science as a profession
In the simplest words, what is Data Science?
The term Data Science is mentioned more and more nowadays, but what really does it mean? In the simplest words, Data Science is a discipline where a huge amount of data is analyzed with application of statistics, mathematics and programming language in order to find answers to complex questions. The complex questions can be of various nature, “How much profit will I make the next year? What is the number of clients that I will gain/lose in the next year? What is the optimal number of products in stock? Which is the optimal way to motivate employees?”
The key word in the term Data Science is not Data, but Science, because in the practical application of Data Science it is actually necessary to find out what each piece of data that we have represents and to interpret it.
What is the difference between Business Intelligence (BI) and Data Science?
The difference between Business Intelligence and Data Science is actually very big and it can be analyzed from several aspects. The first difference is that BI systems are designed to look back, that is, to provide an analysis of what happened in the past, based on real data. Data Science, on the other hand, looks toward the future, that is, to predict what will happen in the future. Also, BI systems provide detailed reports, Key Performance Indicators (KPI) and trends, but do not tell what the data will look like in the future. Traditional BI systems tend to be static and comparative.
They do not offer space for research and experiments. Also, the data sources are static, that is, we have pre-planned sources, which unlike them, in Data Science we have bigger flexibility because the sources can be added as needed and much faster than with the previous ones. BI systems provide a single version of truth, while Data Science offers precision and reliability.
Why is it considered a fast-growing profession of the future?
It is only necessary to do one search on LinkedIn job posts or any of the other job post sites and you will see that one of the most in-demand jobs is Data Scientist. Last year, LinkedIn published a report analyzing data (from the USA) for the period 2012-2017 and the number of advertisements asking for a Data Scientist grew by 6.5 times, which puts this position in the top 5 most sought-after positions. This situation is due to several facts:
- Increased amount of data that is generated: the analysis of huge amount of data requires special skills and knowledge which are characteristics of Data Scientists.
- Decisions based on data are more profitable: for most companies, data is not useful if there is no benefit from it. According to a Harvard study, companies whose decisions are made based on available data are 6 times more profitable than those whose decisions are based on instinct or experience.
- Data Scientists change the work of a company and make it possible to predict the operation in every aspect.
What knowledge and skills are required for a Data Scientist?
Although it is not easy to summarize all the skills and knowledge that a Data Scientist should have, I can say that in my opinion the list of top 5 technical skills and knowledge would be:
- Programming – every Data Scientist must know at least one of the most frequently used programming languages in this area: R, Python or Java and of course programming language for working with relational databases- SQL.
- Statistics – a good knowledge of statistics is also very important. Every Data Scientist should be familiar with statistical tests, distribution, maximum likelihood estimators
- Machine Learning – the next knowledge that the person should have is about machine learning methods such as k-nearest neighbors, random forests, ensemble methods and others.
- Hadoop – this is one of the most commonly used Big Data platforms.
- Visualization – visualization and the use of visualization tools such as Power BI, Tableau and similar to them is more than important.