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Data Science, Data Engineering and Cybersecurity: Reskilling for a Digital World

Summary of discussion

  • Every company has access to lots of data and most are not doing enough to benefit from it. This is why data engineering, data science, and cybersecurity promise a great career.
  • If you are thinking of a career in data, first understand why. Do not choose data only because there are lots of opportunities. This is a new field and it will keep evolving. You have to be passionate and keep upgrading yourself. Learning Python and Machine Learning will not set you up for life.
  • But do not be afraid of change. Look at it as an opportunity and not a threat. Remember that those who would not be able to cope with it will lag behind. If you are a lifelong learner, you can climb up quickly. 
  • A data engineer creates organization-wide access to reliable data. Data warehouse engineer, data platform engineer, data infrastructure engineer, analytics engineer, and data architect are some of the roles under data engineering. Data engineers need to learn SQL, Python, ETL, OS, ML, Hadoop, Spark, MongoDB, and Cloud and IoT tools.
  • Data scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from the data that data engineers provide access to. Some of the data scientist roles are a data analyst, business analyst, ML expert, and data researcher. Data scientists need a strong maths and statistics base and knowledge of Python, SQL, R, ML, and AI.
  • A cybersecurity expert monitors, detects, investigates, analyses, and responds to threats to data. They look for vulnerabilities and plug them. Some of the roles in cybersecurity are information security analyst, security consultant, network security engineer, cybersecurity analyst, and security penetration center, analyst. Cybersecurity experts need to know networking, vulnerability assessment, penetration testing, DB, and system administration.
  • Those who want to become cybersecurity experts should remember that just learning ethical hacking is not enough. You need other skills.
  • Data-driven jobs are not limited to tech companies. Retail, finance, pharma, health, education, and agriculture sectors, including government departments, need data experts. SBI, for example, is already recruiting data scientists.
  • Data has no country, so data careers span cultures and languages. Hence, communication skills are important.
  • Just like data jobs are not limited to tech companies, data careers are not limited to tech students. If you have a passion for data, you can always do courses and change your career path. 
  • Opt for online learning if you are self-driven and cannot take a sabbatical from work. Freshers and those who can take sabbaticals should go for full-time courses as they will give you the opportunity to learn with peers, build networks, and be more hands-on.
  • Glassdoor data shows that data scientists, data engineers, and cybersecurity experts were in high demand in the US in the past four years. Their average salary was $120,000. This is the trend in India too. So if data is your calling, get ready to ride the tide.

Summary of discussion

  • Every company has access to lots of data and most are not doing enough to benefit from it. This is why data engineering, data science, and cybersecurity promise a great career.
  • If you are thinking of a career in data, first understand why. Do not choose data only because there are lots of opportunities. This is a new field and it will keep evolving. You have to be passionate and keep upgrading yourself. Learning Python and Machine Learning will not set you up for life.
  • But do not be afraid of change. Look at it as an opportunity and not a threat. Remember that those who would not be able to cope with it will lag behind. If you are a lifelong learner, you can climb up quickly. 
  • A data engineer creates organization-wide access to reliable data. Data warehouse engineer, data platform engineer, data infrastructure engineer, analytics engineer, and data architect are some of the roles under data engineering. Data engineers need to learn SQL, Python, ETL, OS, ML, Hadoop, Spark, MongoDB, and Cloud and IoT tools.
  • Data scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from the data that data engineers provide access to. Some of the data scientist roles are a data analyst, business analyst, ML expert, and data researcher. Data scientists need a strong maths and statistics base and knowledge of Python, SQL, R, ML, and AI.
  • A cybersecurity expert monitors, detects, investigates, analyses, and responds to threats to data. They look for vulnerabilities and plug them. Some of the roles in cybersecurity are information security analyst, security consultant, network security engineer, cybersecurity analyst, and security penetration center, analyst. Cybersecurity experts need to know networking, vulnerability assessment, penetration testing, DB, and system administration.
  • Those who want to become cybersecurity experts should remember that just learning ethical hacking is not enough. You need other skills.
  • Data-driven jobs are not limited to tech companies. Retail, finance, pharma, health, education, and agriculture sectors, including government departments, need data experts. SBI, for example, is already recruiting data scientists.
  • Data has no country, so data careers span cultures and languages. Hence, communication skills are important.
  • Just like data jobs are not limited to tech companies, data careers are not limited to tech students. If you have a passion for data, you can always do courses and change your career path. 
  • Opt for online learning if you are self-driven and cannot take a sabbatical from work. Freshers and those who can take sabbaticals should go for full-time courses as they will give you the opportunity to learn with peers, build networks, and be more hands-on.
  • Glassdoor data shows that data scientists, data engineers, and cybersecurity experts were in high demand in the US in the past four years. Their average salary was $120,000. This is the trend in India too. So if data is your calling, get ready to ride the tide.
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