Data has become important in today’s digital world. It is present everywhere: from social media platforms to shopping apps, banking, etc. Two important fields are necessary around data: that is Data Science and Data Analytics. They both sound similar but both are quite different from each other. Come and let us understand both of them in a very simple way.
What is Data Science?
Imagine a box that is full of jewels and gold which is locked but you don’t know what is inside a box. A Data Scientist acts like an explorer who uses some tools and skills to unlock that box. He finds the treasures and understands how they can be used.
Key Features of Data Science
- Data science focuses on getting patterns and insights into the data.
- For solving complex problems, Data Scientist uses programming, statistics, and machine learning.
- They also help in future predictions like how a company will grow and what action can be taken.
Example of Data Science
A data scientist at the Netflix platform mainly analyzes the data that people watch with interest and uses that data in future plans for upcoming new shows or movies.
What is Data Analytic or Analysis?
Now you have to imagine that box is already unlocked. Here you have to decide how much gold to use and where to invest. Data Analytics acts like a planner and makes decisions.
Features of Data Analytics
- It focuses on analyzing any data which can be used to solve the problems.
- In data analytics tools like MS Excel, SQL, and visualization software are used which make that data easy to understand.
- It mainly helps in improving business performance by answering questions like, “Why did sales drop last month?”
Example of Data Analytics
A data analyst at the Amazon platform mainly studies customer reviews and sales data to find out why a product is not selling well.
Important Differences Between Data Analytics and Data Science
| Aspect | Data Science | Data Analytics |
| Purpose | Predicts future outcomes and upcoming trends. | Python, R language, etc |
| Skills | Programming, machine learning, and AI. | Data visualization and reporting. |
| Tools Used | Python, R language etc | Excel, Tableau, SQL. |
| Quality | It mainly works on creating models and algorithms. | It mainly focuses on interpreting existing data. |
Which one should You Select for Your Career?
If you love exploring new problems, coding, and creating new innovative solutions then Data Science is the perfect path for you. On the other hand, if you enjoy in organizing information and solving business challenges then you can choose Data Analytics as a career option.
So, if you really want to start your journey in data science and data analytics career then various institutes are offering training for that. You can search for the best institute on Google but still, among them, ADMEC Multimedia Institute is the best training institute providing courses in data science and data analytics for the last 20 years.
Why Choose ADMEC for Your Data Analytics Training?
When we talk about learning these skills then ADMEC stands out. Know why:
- Comprehensive Course Curriculum: We cover everything from basics to advanced topics in both Data Science and Data Analytics. Here you will be prepared as per industry requirements.
- Practical-Based Training: ADMEC mainly focuses on real-world projects to prepare its students for the industry. Our experts are good in leading tools of data analysis like MS Excel, PowerBI, Tableau, Python, and R.
- Expert Trainers: Here you will be trained by experienced professionals who deeply understand the market needs.
- Flexible Classes Options: Both online and offline class options are available so you can choose the mode according to your convenience. We also offer training on weekends for working professionals and students from college.
Many courses in data analytics are offered by ADMEC Multimedia Institute. Here all staff members are very cooperative and experienced. You must attend counseling and demo sessions before joining which will be more helpful for you in making a decision.
