Data science is a method to transform data into valuable business strategies. It is a means to make sound decisions to increase profit, improve the customer journey, and spot opportunities there is much more.
A Data Scientist is also sometimes called Data Analyst and is involved in structuring and analyzing large amounts of data. This is to discover insights that are important for the organization for which he/she works, for example, product development, finance, and management.
They use different technologies, and the Data Scientist can also be described as the engineer of the future. Data Scientists are mostly employed within IT companies, banks, insurance companies, the food industry, and the government.
What Does DATA Scientist Do?
Data scientists can be real changes within an organization and offer insight into how the process of the company can be towards its ultimate business goals. A Data Scientist helps an organization (or department) find the information hidden in vast amounts of data and helps make smarter decisions to deliver even better products or services. The primary focus is on applying data mining techniques, doing statistical analyses, and building high-quality forecasting systems.
To summarize all this
1. Modulate statistics and mathematical calculations. For this, I use for example SPSS, R, and Python
2.Data mining using SQL, NoSQL, Hadoop / Hive
3. Domain research, making connections, asking questions, involving the right people
4.Storytelling, interpreting data, explaining the possibilities, supported by powerful visualizations.
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Difference between a data analyst and data scientist
Data analysis and data science go hand in hand. A data analyst searches for data flows, processes them, and identifies correlations and patterns and reports them. A data analyst collects insights and makes organizations aware of the current state of affairs.
A data scientist goes further than identifying trends. The data scientist delves even deeper into the matter and makes calculations to make predictions about future developments in an organization. A data scientist also has programming skills. He or she is also involved in evaluating current models and building even better predictive algorithms.
And what if you do a data science vs. significant data comparison?
Big data includes all possible data sets from an organization. As described above, this concerns structured data and unstructured data. You need a great deal of expertise to collect structured data. Data Scientists work with various amounts of data. However, big data is their specialty, something that a data analyst often focuses less on. Usually, the more information is available, the more parameters can be included in the models, and so you can make even more accurate decisions. Data science and big data also go hand in hand.
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