DATA SCIENCE – INSIGHTS

DATA SCIENTIST – DATA ANALYST – DATA ENGINEER

If you’re confused with the step to choose a career in Data science, Data needs a huge number of people. There is an “obtuse of opportunities and acute shortage for data professionals“.

Who are these professionals?????

Professionals, who are able to obtain insights and make supervised conclusions from the data available are high in demand in the country like INDIA.

Let’s dive deep into DATA SCIENCE.

Who are DATA ENGINEERS and what are their responsibilities???

Data Engineers are solely responsible for the preparation of data in an organized and quick accessible to the company they are in. Data Analysts and Data Scientists use this data to bring out the insights which can be the solutions for the business to enhance and develop data.

Responsibilities:

1. Create, install, run & maintain data bases along with storing of all related data points.
2. Test and Certify whether the data meets industry requirements and their practical practices.
3. Exploring new management technologies to handle data and tools.
4. Good communication and team spirit to work with relation designers, data architects & software team to reach project deadlines.

Skills required by Data Engineer:

• Technical Skills: one should good at programming to develop test data. Knowledge in distributed computing is essential for parallel programming along with software. Being a software engineer they should be familiar with Agile SDLC, DevOps to develop pipelines for managing data across systems. Obviously data scientist should be an expert in SQL and additional query languages.
• Collaborative Communication: Good at listening data architects, scientists and their management decisions to reach their expectations and the requirements of the organization. Because you are responsible for the data you developed in the organization you are responsible to make data easily retrievable by any other in the organization.
• Intellectual Industry Knowledge: One should be able to understand the working dynamics of the industry and the usage of data, the application of development of data required.

Who are DATA ANALYST and what are their responsibilities???

This includes, analyzing the data and obtaining insights frim the data. Analysts will be dealing with Exploratory data analysis and machine learning techniques for the continuous analyzation of data. Analysts help their organization to know about:

• Marketing strategies & post production sales.
• Optimization of resource usage.

Skills required by a DATA ANALYST:

• Business Domain Knowledge – Data Analysts are business problem solvers. Therefore, they need to have an acute understanding of the business, in order to clearly define the problem and come up with quantitative solutions.
• Analytical and Statistical Skills – Data Analysts operate with large quantities of data, figures, facts and crunch numbers. They need to know statistical and machine learning techniques to analyze the data in order to reach conclusions and be able to make recommendations.  They should be familiar with areas of Exploratory Data Analysis, Hypothesis Testing and Machine Learning.
• Technical Skills: Data Analysts sift through huge amounts of data. They need to know specialized languages like R and Python to perform analysis and be familiar with SQL to manage data and derive quick trends.
• Communication Skills – Data Analysts are often required to present findings or decipher the data into an understandable manuscript. They must communicate complex ideas in the best way possible.

Data Scientists fits in?

A Data Scientist embodies the perfect combination of business knowledge, technical expertise and statistics. As a Data Scientist your job is not to simply draw insights and trends from the data collected over a period of time, but to also create machine learning systems which organizations can deploy final products to automate decision making.

Like other data professionals, as a Data Scientist, you would be expected to know how to retrieve data from varied sources. Additionally, to create algorithms to find hidden trends and patterns, and how to develop appropriate conclusions. Therefore, you will need to know concepts like data preparation and exploration to gather and understand data. Machine learning to create predictive systems. And, a bit of software engineering too in order to create a product.

Skills required for a DATA SCIENTIST:

• Knowledge in algorithms, statistics, mathematics and machine learning.
• Programming languages such as R, Python, SQL, and Hive.
• Business strategies understanding and the aptitude to frame the right questions to ask, and find answers in the available data.
• Communication skills in order to communicate the results effectively to the rest of the team and the end users.

To Conclude:

The Data Engineer looks into the data needs of the organization they are in. Data Analysts provide insights from the data they are working. Data Scientists create data products which can make the user experience errorless. It is important to keep in mind that these roles and responsibilities varies from the organization to organization.

Author:

MIHIR BOMMISETTY