Applied Scientist vs. BI Developer

Applied Scientist vs. BI Developer: A Comprehensive Comparison

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The fields of Artificial Intelligence (AI), Machine Learning (ML), and Big Data have become increasingly popular in recent years, leading to a surge in demand for professionals in these areas. Two roles that are often confused are Applied Scientist and Business Intelligence (BI) Developer. In this article, we will explore the differences between these two roles, including their definitions, responsibilities, required skills, educational backgrounds, tools and software used, common industries, outlooks, and practical tips for getting started.

Definitions

An Applied Scientist is a professional who applies scientific and mathematical methods to solve complex problems in the field of AI and ML. They use Data analysis, machine learning, and Statistical modeling techniques to develop algorithms that can be used to make predictions, automate processes, and improve decision-making. Applied Scientists typically work in Research and development teams and are responsible for designing, Testing, and implementing AI and ML models.

On the other hand, a BI Developer is responsible for designing, developing, and maintaining business intelligence solutions. They work with data from various sources to create reports, dashboards, and visualizations that provide insights into business operations. BI Developers use tools and technologies such as SQL, ETL (Extract, Transform, Load), Data Warehousing, and reporting software to create these solutions.

Responsibilities

The responsibilities of an Applied Scientist and a BI Developer differ significantly. The primary responsibilities of an Applied Scientist include:

• Conducting research to identify and develop new AI and ML models
• Designing and implementing algorithms that can be used to solve complex problems
• Analyzing data to identify patterns and trends
• Testing and validating models to ensure accuracy and reliability
• Collaborating with cross-functional teams to develop and implement solutions
• Staying up-to-date with the latest developments in the field of AI and ML

On the other hand, the primary responsibilities of a BI Developer include:

• Developing and maintaining data warehouses
• Designing and developing ETL processes to extract, transform, and load data from various sources
• Creating reports, dashboards, and visualizations to provide insights into business operations
• Ensuring data accuracy and consistency
• Collaborating with business stakeholders to understand their requirements and provide solutions
• Staying up-to-date with the latest developments in BI technologies

Required Skills

The skills required for an Applied Scientist and a BI Developer are quite different. Applied Scientists need strong mathematical and statistical skills, as well as expertise in programming languages such as Python, R, and Matlab. They also need to have a deep understanding of machine learning algorithms, data analysis techniques, and Data visualization tools.

BI Developers, on the other hand, need strong SQL skills, as well as expertise in ETL processes, data warehousing, and reporting software such as Tableau, Power BI, and QlikView. They also need to have a good understanding of business operations and be able to communicate effectively with business stakeholders.

Educational Backgrounds

The educational backgrounds required for an Applied Scientist and a BI Developer are also different. Applied Scientists typically have a Ph.D. in a field such as Computer Science, Statistics, or Mathematics. They may also have a background in Physics, Engineering, or other related fields.

BI Developers, on the other hand, may have a degree in computer science, information technology, or business administration. They may also have certifications in BI technologies such as Microsoft Certified: Azure Data Engineer Associate or Tableau Desktop Specialist.

Tools and Software Used

The tools and software used by Applied Scientists and BI Developers also differ. Applied Scientists use programming languages such as Python, R, and MATLAB, as well as machine learning libraries such as TensorFlow, Keras, and Scikit-learn. They also use data visualization tools such as Tableau, Matplotlib, and Seaborn.

BI Developers, on the other hand, use SQL for data manipulation and querying, as well as ETL tools such as Microsoft SQL Server Integration Services (SSIS) and Informatica. They also use reporting and visualization tools such as Tableau, Power BI, and QlikView.

Common Industries

Applied Scientists and BI Developers work in different industries. Applied Scientists typically work in research and development teams in industries such as healthcare, Finance, and technology. They may also work in academia or government agencies.

BI Developers, on the other hand, work in industries such as finance, healthcare, retail, and manufacturing. They may also work in Consulting firms or technology companies.

Outlooks

The job outlook for Applied Scientists and BI Developers is positive. According to the Bureau of Labor Statistics, employment of computer and information Research scientists (which includes Applied Scientists) is projected to grow 15 percent from 2019 to 2029, much faster than the average for all occupations. Similarly, the job outlook for BI Developers is also positive, with a projected growth rate of 10 percent from 2019 to 2029.

Practical Tips for Getting Started

If you are interested in becoming an Applied Scientist, some practical tips to get started include:

• Pursue a Ph.D. in Computer Science, statistics, or mathematics
• Learn programming languages such as Python, R, and Matlab
• Gain expertise in machine learning algorithms and Data analysis techniques
• Participate in research projects or internships to gain practical experience

If you are interested in becoming a BI Developer, some practical tips to get started include:

• Pursue a degree in computer science, information technology, or business administration
• Learn SQL and ETL tools such as Microsoft SQL Server Integration Services (SSIS) and Informatica
• Gain expertise in reporting and visualization tools such as Tableau, Power BI, and QlikView
• Participate in internships or work on personal projects to gain practical experience

Conclusion

In conclusion, Applied Scientists and BI Developers are two distinct roles with different responsibilities, required skills, educational backgrounds, tools and software used, common industries, outlooks, and practical tips for getting started. Both roles are in high demand and offer exciting career opportunities for those interested in the fields of AI, ML, and Big Data.