What is Data Science? Applications and approaches

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Contents Data science in a broad sense What is the function of data science in a larger data service? How are some of the big companies approaching data science? How do startups and challengers handle data science? Is there anything data science can't do?

Data science is the application of scientific and mathematical techniques to business decision-making. Specifically, it has become known for data mining, machine learning (ML), and artificial intelligence (AI) processes increasingly applied to very large ("big") and often heterogeneous sets of data. semi-structured and unstructured datasets.

The term was first suggested in the 1970s as a synonym for "computer science", then in the 1980s as an alternate term for "statistics". Finally, in the 1990s, a consensus began to form that data science is an interdisciplinary practice that combines data collection, computational processing, and analysis. It is considered "scientific" because it applies systematic analysis to observable real-world data.

Since then, it has connoted this full scope, from the aggregation of source data to its application in decision-making and technical and business processes.

But it has also become more closely associated with the specialized role and function of "data scientists" in the burgeoning data departments that handle more and more data in the modern enterprise.

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look here Data science in a broad sense

In a broad sense, data science can be thought of as the application of scientific and mathematical techniques to business decision-making. This work can be divided into three broad areas:

Collection: Simply collecting information from disparate IT systems can be a challenge in itself. The data is often in different formats and may contain falsified or incomplete records. When data is cleansed and standardized, it needs to be stored so that data science algorithms can be used again and again in the future. Analysis: Finding patterns and understanding changing requirements at every stage of the business requires a mix of statistical analysis and artificial intelligence. Reports: Reports can summarize activity, flag abnormal behavior, and predict trends and opportunities. Tables, graphs, visualizations and animated sum...