- 12 Sep, 2024
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Is Data Science and Data Analytics are Same or Different
Data science and data analytics are two terms that are often used interchangeably. However, these two terminologies have bright lines that distinguish them. Both handle data but they are different in terms of the methods used and objectives involved.data science vs data analytics.
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Data analytics involves taking large volumes of datasets and drawing conclusions from what is contained in them. It employs computational and statistical techniques to find relationships within data. The purpose of data analytics is to decipher what has happened historically and why it took place.
Some tools used in data analytics include Excel, SQL, and Tableau. The analytics professional excel when work with big datasets, cleaning data, graphical presentation techniques as well as using statistics.
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On the other hand, data science is the wider concept that covers data analytics. Data analytics focuses on past whereas data science focuses both on present and future matters. It entails using scientific methods like statistics, algorithms as well as machine learning to obtain meaning out of information in a computer system or network.
Programming languages that data scientists professional are skilled in include Python and R, as well as databases such as Hadoop and Spark. In addition they have knowledge on advanced statistical techniques, machine learning, and data visualization.
Differences between data science vs data analytics
One of the main differences between data science vs data analytics is the range of their work. The aim of data analytics is to solve specific business problems and extract insights from data to enable organizations make smarter decisions while in contrast, data science aims at creating new models, methods and tools for extracting information from datasets.
Another difference is the level of technical expertise required. While a background in statistics and analysis is essential for a person working as a data analyst, one who wants to be a good professional scientist must have vast knowledge on programming, machine learning as well as visualizing of big datasets.
Data science is also about a lot of concentration on unstructured data sources like images, videos and audios. On the other hand, data analytics usually deals with structured information such as spreadsheets and databases.
Lastly, data science concentrates more on prediction and forecasting. On the other hand, data analytics focuses on what happened in the past and why it happened.
To sum up on that point, data science vs data analytics are closely associated with one another since they both concern themselves with information. Data analytics refers to drawing insights from information so as to resolve particular business issues while data science comprises development of new methods as well as tools for analyzing it. Both fields require a strong background in statistics and data analysis; however, the field of data science requires more advanced technical skills such as machine learning and programming.
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