High technology and good internet services have made it possible for a business to work efficiently that produce data in large amounts. This large group of data is called Big data. The data is put to use to extract meaningful information from data.
Over the years, big data have increased so much that the traditional methods of data analysis and extraction are not producing significant results.
In different terms, there is also to it that is missing. So data science here comes into play which promises advanced techniques and concepts of using data. Data science consulting services have seen growing importance over the years because it has helped make significant business decisions.
Also, it has automated repetitive, time-consuming tasks with the help of machine learning and AI. All these methods result in better operations of the business, which overall improves the wealth of the organization.
Curious to know why Data Science has proven beneficial to organizations? This article explains data science and why taking up a Data Science online course is a worthy option.
1. Who is a Data Scientist?
So far, we have known why data science has seen growing importance. Therefore data science is the application of advanced methods and concepts of extracting meaningful information from data and putting it to the user for business decisions.
Consequently, the data scientist is the professional who practices the tools and techniques of data science and applies them to resolve business challenges. The skills required to become a data scientist are listed below:
- Statistical methods and tools: Analyzing the data is the critical initial step.
- Machine learning: building algorithms and implementing them so that the computer/software automatically learns from them.
- Computer science: database systems, artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering.
- Programming: computer programming languages such as Java, R, Python, and SQL are the languages used popularly for data science. The algorithms are constructed with its help of it.
- Data storytelling: communicating the process involved in simplified terms to the non-technical audience.
- Business intuition: connecting with all the involved stakeholders to dig deeper into the business challenges and find long-term solutions.
- Analytical thinking: finding analytical solutions to abstract business problems.
- Critical thinking: before concluding, make sure that the objective analysis is performed.
- Inquisitiveness: digging deeper into the resources to discover more about the solutions.
- Interpersonal skills: communicating the work with all the levels of the organization.
2. Roles and Responsibilities of Data Scientist
The roles and responsibilities that a data scientist performs are listed below:
Data Analysis
It is a crucial initial step that data scientists take. It involves analyzing data with the help of statistical tools and techniques. The more analysis is done, the better decisions are taken. Some of the data mining techniques, such as pattern detection, graph analysis, decision trees, clustering, or statistical analysis, are important.
Work with Stakeholders
The data scientist observes the techniques and resources used to take out data and what system is being followed for its use. After that, he collaborates with the people involved in these processes.
This is beneficial because the data scientist gets to know detailed information about where the data is being utilized and in what ways.
After getting to know the details of the data, the next step is the creation of data models databases, big data, etc. Here also, the different stakeholders should be made aware of all such work. Involving them will lead to better solutions in the future.
They advise companies on their data potential. Searching for new insights and then transforming them into business goals. They are performing advanced statistical analysis, data mining, and visualization technologies.
Collaboration with stakeholders requires you to have some essential communication skills. Make sure that the information you are trying to find out is available in the sources that you believe. Ask questions and try to extract more information about the data so that the problems are solved effectively.
A data scientist is different from a data analyst. While data scientists also analyze data with the help of statistics, their work has more to it. They apply a creative and artistic approach to their work processes. They believe in getting data from multiple resources and believe in acquiring ideas from out of the box also.
3. Conclusion | Role of a Data Scientist
We know that the work of data scientists is spread across vast areas; after all, it’s quite a challenging and demanded role across companies.
According to payscale, the standard payroll of a data scientist is ₹698,413 in India. The top companies that hire data scientists are Microsoft, Facebook, IBM, Amazon, Google, Apple, and Oracle.
This shows how much data science is essential, and organizations are willing to pay a reasonable amount for it. That’s why, if you are a computer science graduate or a statistician, or even a management student, you can start a career in data science.
All it requires is learning the right amount of skills from industry experts and participating in real-time projects. You can enroll in an online course which will be cost-effective as well as you need not worry about the location, which becomes an obstacle sometimes.
Tech Trends
Related posts
Leave a Reply Cancel reply
Hot Topics
Categories
- Ads (5)
- Animes (25)
- Artificial Intelligence (AI) (33)
- Augmented Reality (AR) (10)
- Automotive (9)
- Bitcoin (15)
- Blockchain (22)
- Business (239)
- Business Intelligence (2)
- Cloud Computing (23)
- Computer (127)
- Cryptocurrency (9)
- Cybersecurity (36)
- Data Science (9)
- Database (4)
- DevOps (6)
- Digital Marketing (72)
- Digital Workplace (14)
- Ecommerce (1)
- Education (28)
- Electric Vehicle (EV) (1)
- Electronics & Hardware (16)
- Entertainment (42)
- Fabrication (3)
- FAQ's (1)
- Finance & Marketing (46)
- Gadgets (34)
- Games (8)
- Gear (29)
- Industry (42)
- Information Technology (86)
- Internet (409)
- Internet of Things (IoT) (40)
- Job (25)
- Machine Learning (4)
- Marketing (87)
- Mobile Apps (20)
- Movies (11)
- Natural Language Processing (5)
- News & Trends (102)
- Programming (4)
- Science & Technology (226)
- Security (73)
- SEO (54)
- Services (36)
- Social Media (70)
- Software (96)
- Sports (1)
- Technology (297)
- Telecom (6)
- TikTok (5)
- Tours & Travels (9)
- Uncategorized (11)
- Virtual Reality (VR) (7)
- VoIP (4)
- Web Technology (40)
- Workforce (17)
- Workspace (6)
Stay connected