How do I Start a Career in Data Science?

Data Science

Do you know how internet shops recommend various goods for you to purchase? Exactly how does Instagram display the pages you're interested in?

Many questions occasionally cross our minds. In practise, it is impossible to do so without the necessary data. Massive volumes of data are used in data science to tackle any issue. Making the appropriate choice could be challenging.

Take a suggestion that demonstrates the value of speculating on who the next US president will be.

However, a data scientist's primary responsibility is to fully comprehend the data. After gathering the data, he must extract the pertinent and important information that will be utilised to address the issue.

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The Life Cycle of Data Science

• Define the Problem Statement
• Data Collection
• Data Quality Check
• Exploratory Data Analysis
• Data Modeling
• Data Communication

• Step 1

  Define the Problem Statement

  To start, you must identify the issue statement that has to be resolved. It's much simpler to fix a problem if you identify the appropriate one.

• Step 2

  Data Collection

  The second step is to collect data because without data you cannot solve the problem. For this purpose, you may need primary or secondary data. If the data is not available anywhere and you have to dig for it, then its preliminary data, and if it's available somewhere, then it is called secondary data.

• Step 3

  Data Quality Check

  It is crucial to assess the data's quality once it has been gathered to determine its reliability and the veracity of its source. You won't be able to fix your problem if you overlook this element.

• Step 4

  Exploratory Data Analysis

  The fourth step is to analyze the collected data. It is a difficult step in which you have to extract the critical information which can be the solution to your problem. You can use graphs for your help.

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  Step 5

  Data Modeling

  One must list every method employed to solve the problem in the fifth phase. The approach must be chosen as the first crucial step.

• Step 6

  Data Communication

  The last and final step is to communicate the results to the stakeholders. One must know the simple, understandable language because they are not professionals they may not understand the professional/industry jargons.

Why should one take it as a career?

There are several benefits to choosing data science as a profession. Modern society produces a lot of data as a result of digitization, and experts in data science are required to handle, assess, and extract usable information from data.

On the employment market, there is a strong need for data scientists. It is a wise decision to pursue it professionally since, as data creation rises, so will the demand for data scientists, creating millions of new opportunities in the field.

• According to NASSCOM, 1.4 lakh jobs are available in data science.
• In 2021, there is a noticeable deficit of data science professionals by 2.3 lakh.
• In 2018, demand for professionals had increased by 417%
• According to Glassdoor, the best job to pursue as a career in data science

Is Data Science Certification worth it?

Around the world, data science is producing a large number of employment. company organisations are employing data scientists to analyse the data and enhance company operations. There is a huge need for data professionals, but their pay are too costly. The finest employment in the industrial sphere are thought to be those of data scientists. Since online data creation is expanding at an unprecedented rate, this vocation will likely be long-lasting.

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