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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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Related Questions

Hi, I am Anand having 4 years of experience in IT Recruitment but I have interest to build my career in HR Data Analytics. Please do let me know if anyone can help me on this?
Hi Anant, Try to make your future in Data Analytics, it will be good. Thanks - Syed.
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Hi, I am looking for a managerial position in health care analytics sector. I have a background of Bachelors in Occupational Therapy and a Masters in Public Health Administration. I have more than 7 years experience of working with public health data, bio-statistics, epidemiological analysis. Currently working as a Sr. Epidemiologist in Hyderabad. I have an expertise in disease forecasting and scientific writing. Please suggest what course I should take up to become an expert in health care analytics domain, so that I can apply for mid level managerial positions. I am currently based at Hyderabad.
you consider "Healthcare Analytics Certificate Program" by UC Davis. Refer to https://extension.ucdavis.edu/certificate-program/healthcare-analytics-certificate-program
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Hi, currently I am working as associate systems engineer. But I am really interested in data science. How can I become a data scientist. Please suggest me a path.
Let me comprehend based on my 20 years of working experience. You need to know few things to become a data scientist. 1) Statistics and Mathematics : It is like a doctor having good understanding of...
Vamsi
I have been in the teaching field for 4+ years working as an assistant professor now I need to get into a software field. Basically, I doesn't know much about programming. I need suggestions on which field it would be good.
Narasimha,What i think is programming is not only related to language but moreover its a logic. If have better understanding and clear conpect that what you want to buil and how you built then you can...
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What background is required for data science?
Data science includes AI ,MachineLearning ,Satictics, presentation technique and deployment tools . DS helps to predict the future trends, what measures can be taken. Anyone with python programming, Statistics and presentation skill.
Shivani
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