Data science is evolving as one of the most promising and reliable career paths for professionals. Consequently, today’s successful data professionals understand that they need to overcome traditional big data analytics, data mining, and programming skills. To reveal helpful information for an organization, data scientists have the full range of the data science lifecycle and a level of flexibility and understanding to maximize profits at every stage of the process.
The term “data science” was introduced in 2001 by William S. Cleveland, a respected professor specializing in computer science and statistics at Purdue University. Data science is a technical term that includes a combination of tools, business insights, algorithms, and machine learning to extract insights and information from raw data.
Tools used to analyze and generate forecasts range from SAS, Apache Spark, and Tableau. SAS is a leader in business analytics, and the demand for SAS data scientists is increasing. Apache Spark is a popular alternative, especially for companies that use machine learning models to understand their data. In explaining why data science is essential to the collection and processing of information, Investopedia states: “Data science provides meaningful information based on large amounts of complex and big data. Data science or data-driven science combines the work of different disciplines of statistics and computation to interpret data for decision-making purposes. Check out the program on data-driven decision-making, which would help you better understand the subject.
Social media, blog posts, and product page traffic need to be gathered in a way that accelerates business growth, from the acquisition of internal data for customers, patients, products, or services to the acquisition of such external data. Data science aids to support your company’s vision, strategy, and roadmap.
Future of Data Scientist
The future of data science is bright for experts in this field as they learn to work with advanced AI methodologies and technologies. The reason is that technology is advancing rapidly and integration within the enterprise is high, while the major obstacle for the enterprise is in the form of talent to drive AI initiatives. A study by EY and MIT Technology Review suggests that the most significant barrier for companies to adopt AI was the slowdown in recruitment due to the lack of skills of adequately qualified people. About 60% of respondents say they don’t have the skills to manage AI programs.
Essential Skills for a Data Scientist
Mathematics: Linear algebra, calculus, and statistics. All data science models are based on their number and quantity. Therefore, it is essential to understand statistics in order to learn how to calculate numbers. Calculus is also necessary, as the numbers are constantly changing, and many of the results involve finding the derivative. Other important aspects include, but are not limited to, cost functions, scalars and vectors, matrices and tensor functions, and gradients and derivatives.
Data Processing: All data that reaches your organization is raw and needs to be converted to numbers for further investigation. Then, there are steps to map the data and remove any noise that has not been added to the data. Data processing is itself a skill required to understand the tools and techniques used by data scientists.
Cloud Computing: Cloud computing replaces centralized systems in terms of both data storage and computing power. Cloud computing and data science are almost inextricably linked today due to the widespread use of cloud platforms such as AWS, Google Cloud, and Azure in the industry. Data scientists need to understand the utilization of products offered by cloud services for their daily tasks, using data such as data analytics, visualizations, and other tasks.
Communication Skills: Strong communication skills are absolutely essential non-technical skills that data scientists must possess. As their role expands, they need to interact with internal teams and stakeholders to communicate and lead the project effectively.
The Road to Becoming a Data Scientist
Data science is a broad field having various applications, and the latest generation is heavily inclined to it. There is no specific qualification, but the path to that qualification begins for many in software engineering. Programming skills acquired with a bachelor’s or master’s degree can significantly increase the potential of a graduate’s promising career. Simultaneous participation in a data science degree can significantly improve your career prospects and facilitate the transition to professionals with industry-related qualifications for professionals. Skills are more important than graduation in this area, so there are some prerequisites to check before considering becoming a data scientist:
- Have a degree in computer science or a similar or related degree.
- Practical knowledge of programming and operation of software such as Python, Hadoop, Pig, and SQL is required.
- You need to have good leadership and business skills.
- A complete understanding of mathematics and algorithms is necessary.
- A drive to solve the problem and understand the broader context of the data is vital.
Obtaining a Data Science Certificate
As an emerging field, data science is still in its infancy. According to the SeedScientific survey, the world is expected to generate 175 zettabytes of data by 2025. A degree to become a data scientist is the first step towards a rewarding career. Obtaining a data science certificate is necessarily an essential qualification that will lead to full-time employment in this area. Therefore, the future of data science has a broad scope for all industries and aspirants seeking a career in this discipline. Skilled talent is the need for time and the future for companies hiring people who can build technology and work with advanced systems based on artificial intelligence.
In summary, it isn’t easy to decide whether to choose a certification course. You are endangering your time and money in the hope of building a new career. Choosing the right course and developing your skills is a strong bet. The certification itself is of no value unless the skill complements it. Always look for courses that add value to your skills, not just certificates. Data Science online training offered by Great Learning will guide you through the right path in developing cutting-edge skills.
The future of data science is bright for those with the right skills to pursue it professionally. Data science will revolutionize multiple sectors through artificial intelligence and automation, such as healthcare, transportation, business, finance, and manufacturing. I hope this article has answered all your questions.