What are the key components in Data Science ?

Question

The key components in Data Science are data collection, data processing and cleaning, exploratory data analysis, statistical analysis, machine learning, data visualization, and communication of results.

Tolulade Ademisoye · Accepted Answer

@ruhi_parveen Word/Text analytics, Pattern analysis, trends, operations research, and even AI can be said to be in data science according to SAP IBM.

Tolulade Ademisoye · Answer

you've mentioned some key components already.

priyanka rajput · Answer

Data science comprises key components such as data collection from diverse sources, data cleaning to ensure accuracy, and exploratory data analysis to uncover patterns. Statistical analysis and machine learning techniques are then applied to extract insights. Data visualization helps in presenting findings effectively, while deployment and communication ensure that insights are implemented and communicated to stakeholders. These components collectively empower organizations to harness the full potential of data for strategic decision-making and innovation in various fields including business, healthcare, finance, and beyond.

Ruhi Parveen · Answer

@ato1
Apart from this do you know some more key components
so please tell me

shakyapreeti · Answer

The key components of Data Science are:

Data Collection: Gathering raw data from various sources.

Data Cleaning and Preprocessing: Ensuring data quality by removing errors and handling missing values.

Data Analysis: Exploring data to identify patterns and relationships.

Statistical Modeling: Applying statistical techniques to make predictions or inferences.

Machine Learning: Using algorithms to build predictive models.

Data Visualization: Presenting data insights through visual representations.

Communication: Effectively sharing findings and insights with stakeholders.

What are the key components in Data Science ?

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