It is important to study the concept of “Business Analytics” and “Data Science” in order to understand the role each one plays. In this guide, I will explain briefly what you need to know about Business Analytics and Data Science.
About Business Analytics
Business analytics is the process of guiding businesses to improve the procedure of product production and services through data analysis. It performs a crucial role across the business and information technology industry.
It involves the collection and analysis of data across several business models. Each data findings are also communicated across different platforms such as Excel, SQL, and Tableau. Business Analysts Training provide data-driven reports and recommendations for the growth of a business. They are mostly responsible for managing business models and providing support for businesses through their decision-making skills.
What is Expected of a Business Analyst
As a business analyst you are expected to learn fundamental data skills that can be applied across several industries. Example of these skills are;
- Building business models with Excel.
- Analyzing data with Excel.
- Using SQL for Database Query.
- Executing variance analysis.
- Handling business forecasting and budgeting.
- Creating informative data visualization with Tableau.
- Applying designs and building data dashboard.
- Outlining problems and creating solutions for businesses.
- Providing business requirements and reports for stakeholders.
Business Analytics Jobs
The various Business Analytics jobs available are;
- Business Management Analyst
- Agile Business Analyst
- Business Solutions Analyst
- Business Performance Analyst
- Business Intelligence Analyst
- Systems Business Analyst
- Technical Business Analyst
- IT Business Analyst
Each of these job titles comes with its expectations but one fact about them is the fact they are highly lucrative. An average business analyst can earn an average of $60,700 – $90,200. Ensure you research more on Business Analytics.
About Data Science
Data Science involves the collection of data, analyzing and storing of data as well as managing the data to provide companies with a data-driven analysis that shapes their business decision making.
There are several disciplines involved in Data Science such as Computer Science, Data Analysis, Statistical Analysis, and Machine Learning.
Employers in the data science field lookout for different levels of experience when hiring which makes it important for every data scientist to develop specific skills in an area of interest. However, you don’t have to be an expert across all disciplines to land a good job in the field.
What is Expected of a Data Scientist
- A data scientist must understand how to make use of basic programming tools to solve data science-related issues.
- A data scientist should be able to handle data visualization and data communication across different platforms.
- A data scientist should have a good knowledge of statistics, machine learning, and software engineering.
- A data scientist should be able to handle data intuition and data wrangling.
Data Science Jobs
Here are three major Data Science jobs;
- Data Engineer
A data engineer specializes in setting up data infrastructures for business models. An increase in data traffic can lead to organizations encountering difficulties when analyzing data received. So, the need to employ a data engineer is very essential.
If you want to apply for a job as a data engineer, you need to master your software development skills which will help you solve the challenges of companies faced with a large increase in data accumulation.
- Data Analyst
The job of a data analyst is lucrative and in high demand, because they offer a wide range of skills such as transforming and manipulating large data sets to help achieve the business goal of a company. Companies and organizations constantly seek the assistance of data analysts to help them solve data science-related challenges. Their role includes;
- Working as an Excel expert
- Producing data visualizations
- Managing SQL database
- Analyzing results on a company’s dashboard
The role of a data analyst is very similar to that of a data scientist.
- Machine Learning Engineer
This is a special skill set that is academic-oriented. It requires basic knowledge of mathematics, physics, statistics, and programming languages. If you’re wondering why companies need machine learning engineers, why not take a closer look at the need for producing data-driven products.
Organizations that need the role of an MLE are companies that deal with a large database of consumers or provide data-based related services. A good machine learning engineer will provide an excellent data analysis platform for a company no matter how massive the data received from various sources.
Other Data Science jobs are;
- Machine Learning Scientists
- Business Intelligence Developer
- Infrastructure Architect
- Applications Architect
- Data Science Generalist
The role of a data scientist is broad and the job opportunities available are quite enormous. A hiring company will look out for specific skill sets and experience levels when hiring data scientists. Ensure you check out the job descriptions and expertise level before applying for any data science job to know if you’re qualified.
Which One is Better – Business Analytics or Data Science
After an extensive breakdown of Business Analytics and Data Science, it is important to understand that Data Science offers much more benefits than Business Analytics. Business Analytics is crucial for the growth of any business but the benefits of Data Science cuts across every profession in the world.
Over the past few years, it is recorded that Data Science related jobs have been rated as some of the top jobs in the United States. The “U.S Bureau of Labor Statistics” has reported that Data Science Skills will help drive a high increase in employment rate by the year 2026. This increase in employment rate can be as high as 26.5 – 28.0 percent which is quite high when compared to the impact of other professions.
Data Science is crucial in the world of technology. It also enables consumers of products and companies that supply such products to enjoy great benefits. It influences a healthy purchasing habit which ensures consumers enjoy the best of services from clients and businesses.
Data Science also improves public health by providing humans with health and fitness trackers that help in adopting a healthy lifestyle. It also helps prevent potential health issues and assists health practitioners with accurate diagnosis and finding cures for diseases. We can see its importance in helping to reduce the spread of coronavirus across different nations during this global pandemic.
Data Science is also useful in agriculture because it helps farmers to execute proper food production and supply. It also helps in providing proper storage for farm products which reduces food wastage that can lead to food shortage.
You can make the next big move by starting a career as a Data Scientist because there’s a serious lack of competent data scientists and companies are constantly hiring professionals in the field of Data Science. If you know your stuff in this field, you’ll be highly sought after wherever you go. Isn’t that amazing? Certainly. Finally, it is crucial to acquire the necessary skills and certifications before you can qualify to apply for certain roles in the industry. An advanced degree acquisition in Data Science will also help you build a very successful career in the field. Don’t hesitate to give it a try.
