WHY YOU SHOULD VENTURE INTO A DATA CAREER.
Tags: data, datascience, python, dataanalysis
Published: 2023-08-03 14:35:19

Hello, we are all aware that the field of tech is evolving and growing widely, and with that in mind, one should be triggered and beware of the path they should take in their tech career. I am a data analyst and scientist, and I often find myself submerged in the world of data. Based on my experience working in the data field, data is the future, why? Because data does not lie. This article is not to discourage those who have taken a different career path from data but to help those trying to figure out their career in tech or the transitioners in tech.

Before we explore the reasons why one should consider a data career, let’s see the main characteristics one should have before taking a career in data:

**BE READY TO LEARN AND BE PATIENCE**: Data can be overwhelming, many times we deal with huge datasets having thousands of rows. One can easily get confused and lost on how to go about it. For beginners, it is best if you begin with small datasets with only a few thousands of rows.

**UNDERSTAND BUSINESS ACUMEN**: Even without much knowledge in using the required tools in data, one should be able to understand the problem statement, one can never write good queries or codes without understanding what they will achieve after executing the codes.

**BE A PROBLEM SOLVER**: Being a data expert requires problem-solving skills, the aim of being an expert in the data field is to solve real-world problems, therefore hone your skills in problem-solving. You can only solve problems if you get a deeper understanding of the problem.

**ACQUIRE THE RIGHT TOOLS USED IN DATA**: Data careers are wide and are growing rapidly, I would highly recommend anyone wanting to venture into data to first get data analysis skills, get hands-on Excel, SQL(Structured Query Language), Power Bi, Qlik, Tableau(any visualization tool you are comfortable with) and Python it will be an added advantage.

**DATA SCIENCE TOOLS**: Understanding the fundamentals, and knowledge of Python and its libraries is required(pandas, numpy, sklearn, seaborn) understand the fundamentals of machine learning, supervised and unsupervised learning, and the models used in each.While in the processing of understanding the models dig deep into data cleaning, data processing (label encoding, one-hot-encoding), feature selection/engineering, model selection/ training, and model evaluation. Get hands-on competitions, hackathons, and datathons.

_We can explore the importance of one getting into the data field:_

**HIGH DEMAND**: Data is the backbone of modern businesses, and there is a significant demand for skilled data professionals across various industries. Data-driven decision-making has become crucial for organizations to gain a competitive edge.

**LUCRATIVE CAREER PROSPECTS**: Data professionals, such as data analysts, data scientists, and data engineers, often enjoy competitive salaries and attractive career growth opportunities due to their specialized skill sets.

**SOLVING REAL-WOLD PROBLEMS**: Working with data allows you to tackle complex challenges and find solutions to real-world problems. Data analysis helps identify trends, patterns, and insights that can drive meaningful change and improve processes.

**INNOVATION AND IMPACT**: Data professionals play a vital role in driving innovation and technological advancements. They contribute to groundbreaking discoveries, predictive modeling, and AI applications that impact various aspects of our lives.

**CONTINUOUS LEARNING**: The field of data is dynamic and ever-evolving. This presents an opportunity for continuous learning and professional development, ensuring that your skills remain relevant and up-to-date.

**VERSATILITY**: Data skills are transferable across industries, giving you the flexibility to work in different sectors, such as healthcare, finance, e-commerce, marketing, and more.

**DATA-BACKED DECISION MAKING**: By working with data, you can influence critical decisions within an organization. Your insights can guide executives and stakeholders to make informed choices based on concrete evidence.

**JOB STABILITY**: The demand for data professionals is projected to grow steadily in the coming years. This provides job stability and job security in an increasingly data-driven world.

**GLOBAL IMPACT**: Data professionals contribute to solving global challenges, such as climate change, healthcare improvements, and social issues. By using data effectively, you can be part of initiatives that make a positive impact on the world.

**DIVERSE CAREER PATHS**: The data field offers a wide range of career paths. Whether you are interested in statistics, machine learning, data engineering, or business intelligence, there is a role that aligns with your interests and skills.

**BELOW ARE SOME RESOURCES FOR DATA SCIENCE I FIND VERY RESOURCEFUL**:

[HackerRank](https://www.hackerearth.com/practice/machine-learning/prerequisites-of-machine-learning/basic-probability-models-and-rules/tutorial/)

[DataHack](https://datahack.analyticsvidhya.com/contest/all/)

I hope this article was helpful to anyone who read it I will keep updating my articles.

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[LINKEDIN](https://www.linkedin.com/in/naomi-mutheu/)

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