Business Intelligence Developer
Data science was introduced in the 1990s but today it has become one of the most prominent fields of study and application. With the growth of business and industries, data science has been helping it grow more. Data science allows businesses to acquire more information and collect various outlooks.
What is data science all about?
Data science is a branch of science that deals with a massive amount of data in an organization. It is a mixture of algorithm development, technology, data inference.
Organizations now demand skilled data scientists or data analysts who can retrieve valuable insights from raw or unorganized data.
Data science has a huge contribution in all the organizations(private/public/non-profit sectors) and including the popular online marketing platforms like Amazon, Netflix, e-commerce websites, etc. They gather insights through data mining to understand and segregate the customers according to their interests and preferences.
Role of a Data Scientist
The initial and most critical role of a data scientist is to collect a massive amount of data, analyze it and then draw out meaningful insights with the assistance of tools like R, SAS, Python, etc. The functions of a data scientist are listed here:
⦁ Structure the raw data into meaningful and valuable insights(through tools).
⦁ Retrieving a large amount of data from various sources.
⦁ Generate a data visualization for a better understanding and view.
⦁ Create a business model from the gathered insights.
⦁ Improving data collection methods for establishing analytic systems.
⦁ Extending the data with third-party information sources.
⦁ Setting up an automated system to track their performance.
⦁ Making use of a machine learning framework to carry out the smooth numerical computation.
Skills Data Scientist possess
A certified data scientist must possess skills that are essential to progress in the market.
The core skills are:
1. Data collection and preparing them for a better and valuable analysis.
2. Familiarity with the various analytics platforms.
3. Use simple and effective codes.
4. Apply machine learning and artificial intelligence properly.
5. Apply mathematics and statistics in the process.
Why choose data science for a good career?
In today’s era tons of data is generated as the use of the internet is tremendously increasing. There are almost 3.5 billion searches on Google and besides that millions of posts and videos on social media, Youtube, etc. At present, Data science is one of the top career options in the world. That is why more and more people are focusing on this career option to get a promising future.
With the contribution of data science, many organizations have produced valuable insights and improved their customer experience. Also, data science helped companies to make better business decisions depending on the tracking, measuring of the performance metrics.
Data scientists are in high demand in all industries including banking & finance, manufacturing, healthcare, insurance, telecommunications, automobile, etc.
Companies hiring Data Scientists – Companies like Google, IBM, Deloitte, Amazon, Accenture, LinkedIn, Fractal Analytics, and many more.
The expected package for this job can be:
1-4 years of experience – An average total compensation of ₹773,701
5-9 years of experience – An average total salary of ₹1,363,802
10-19 years of experience – An average total salary of ₹1,827,036
Job roles under Data Science
1. Data Scientists- The initial function of a DS is to withdraw valuable information from structured and raw data with the help of programming tools. They maintain the overall database and make them presentable.
2. Data analysts- As the name suggests, they analyze data, build up a model based on their study. Then, they have expected to make data visualization convert their research into a structured report that is understood by the organization.
3. Data Architect- Firstly, a data architect makes sure that the data provided is secure , accessible to the stakeholders. Also, they organize, maintain, and protect the client’s data.
4. Data Miner – They extract the data from the huge databases and then improvise them. They build up and maintain the software.
5. Data Engineer – They study the data completely, build up models and algorithms so that the raw data is easily accessible to the stakeholders. They must have good communication with the clients in order to understand their needs.
6. Project Manager – The project manager is responsible to look after the proper execution of the project. They act as a bridge between the team members and the client to monitor the requirements and changes in the project.
7. Data statistician- This is also an essential job role that is the extraction of data using statistical methods and analyzes them and determine the accuracy of the data.
Business Intelligence Developer