What kinds of problems does a data analyst solve?

Question

In the context of this lesson, what kinds of problems does a data analyst solve?

Answer

The types of problems that data analysts work on can depend on different things, such as the context of the field they are working in, which can include finance, e-commerce, real estate, and many different fields that data plays an important part in.

For example, in the context of business, some common types of problems that data analysts work on are discovering trends in the data to choose the best course of action and strategies to provide the most benefit to a company.

Or, in the context of e-commerce companies, data analysts may try to figure out what ads to show that will have the highest click rate, based on user habits and preferences.

In addition, data analysts in the field of real estate may be determining the price of houses in 5 or 10 years from now, based on current data and trends.

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hy, a question please!!
what is the most important types of company recruiting data scientist ( is it banks and insurance company) ???

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the beast will shine and then ill be the best person in the world.
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Are there any freelancing opportunities in Data science ?

And , what is difference between Data Scientist and Data analyst?

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@prateekjain015133619 am still in my discovery phase too but in a lay man’s language this is how i differentiate the two; Data Analysts have the skills needed to communicate “Here’s what’s happening with the data” and Data Scientists have the skills needed to communicate " Here’s what’s happening with the data, what may happen in the future, and what we might want to do with it." Hope this is helpful.

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Yes Kaggle hosts Kaggle Competitions where several people sign up to compete to win a monetary prize to solve real world problems or come up with solutions for companies that range from small startups to large companies like Google etc.

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Every company is looking for data scientists. Especially companies whose contracts consist mainly of govt contracts.

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The type of problems that can be solved using “big data” based analytic methods deal primarily with demographic study based issues. These issues cover such things as indicate how a particular group of people in a particular area will vote, what they will shop for, what their house hold incomes are, how much education they will most likely have, how long they will live on average and the types of medical problems they are most likely to develop in their life time. These are but a small selection of the possible uses of the results of “big data” analytic methods attempt to answer by using statistical mathematical methods of analysis.

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Would a UX Quantitative Researcher have similar skills as a data analyst/scientists?

you tell the differences very goood

No not totally, UX researcher is a different path than data analyst/scientist , although some basic skills are same like problem solving, programming which are needed in both, data science deals with analysis and working with data using tools like Python libraries, SQL etc

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@array0371972880 thanks for sharing Kaggle! I just signed up and it seems awesome!

What are some examples of industries that rely heavily on data analysis and commonly employ data analysts and data scientists?

This is by order out of my experience…

  • Technology: Tech companies, including those in the software, hardware, and telecommunications industries, use data to develop and improve their products and services. Data scientists can help these companies to identify patterns in customer behavior and usage, as well as to optimize algorithms and systems.
  • Finance: Banks, insurance companies, and other financial institutions use data to manage risk, make investment decisions, and identify new opportunities. Data scientists can help these companies to analyze financial data, develop predictive models, and improve fraud detection systems.
  • Healthcare: Healthcare companies use data to improve patient outcomes, develop new treatments, and reduce costs. Data scientists can help these companies to analyze patient data, develop predictive models for disease diagnosis and treatment, and identify opportunities for process improvement.
  • Retail: Retail companies use data to understand customer behavior and preferences, optimize pricing and inventory, and develop personalized marketing campaigns. Data scientists can help these companies to analyze customer data, develop predictive models for sales forecasting, and optimize supply chain management.
  • Consulting: Consulting firms work with a variety of clients across industries to help them solve business problems. Data scientists can help these firms to analyze data from clients and develop recommendations for process improvement, cost reduction, and revenue growth.
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Is there any portal for Data Science jobs? I am very curious to start with, atleast intern.

Thank you for this helpful response. Been meaning to take Data Science but giving me second thoughts considering I’m from a non-US country and would prefer working remotely.

What about data scientists in Education? Higher education, curriculum development, instructional design? Maybe enrollment data?

A data analyst is able to make sense of the company’s data. And throughout she/he can totally know how to solve any problem in the company.

I haven’t seen any examples of Data Analysis being applied to environmental issues. Is there any scope for a data analysis job in such a field?

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With Chat GPT’s code interpreter release , i believe this data analysis and analyst field gonna change completely

It is also being noticed that it can do machine learning as well , its quite concerning but again its still in beta

Storm is yet to come…Although it can be used to fast up projects and all