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What is the difference between working in analytics and data science?

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Data science is an umbrella term for a group of fields that are used to mine large datasets. Data analytics software is a more focused version of this and can even be considered part of the larger process. Analytics is devoted to realizing actionable insights that can be applied immediately based on...
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Data science is an umbrella term for a group of fields that are used to mine large datasets. Data analytics software is a more focused version of this and can even be considered part of the larger process. Analytics is devoted to realizing actionable insights that can be applied immediately based on existing queries.

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My teaching experience 12 years

While there can be overlap between the two, the main difference lies in their focus and scope. Analytics typically deals with interpreting historical data to uncover insights and make data-driven decisions, often using tools like Excel, SQL, and visualization software. Data science, on the other hand,...
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While there can be overlap between the two, the main difference lies in their focus and scope. Analytics typically deals with interpreting historical data to uncover insights and make data-driven decisions, often using tools like Excel, SQL, and visualization software. Data science, on the other hand, involves more advanced techniques such as machine learning and predictive modeling to extract insights and make predictions from data, often requiring programming skills in languages like Python or R. Data science tends to be more focused on predictive modeling and algorithm development, while analytics is more about extracting insights to inform business decisions. read less
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Data Analyst with 10 years of experience in Fintech, Product ,and IT Services

In easy terms:- **Analytics** looks at past data to understand trends and patterns for decision-making.- **Data science** goes further, using advanced techniques to predict future outcomes and prescribe actions. So, analytics is like looking in the rearview mirror to understand where you've been, while...
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In easy terms:
- **Analytics** looks at past data to understand trends and patterns for decision-making.
- **Data science** goes further, using advanced techniques to predict future outcomes and prescribe actions.
So, analytics is like looking in the rearview mirror to understand where you've been, while data science is like looking ahead, using what you know to plan for what's coming. Both are important for making informed decisions, but data science is a broader field with more advanced tools and techniques.

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