Overview of data analytics VS data scientist

• Data analytics is crucial in deriving actionable insights by analyzing existing datasets. This examined and derived data is involved in making essential business decisions. 

• Data science is broad because data scientists build models and algorithms to predict future trends. 

• Though data handling is the common root of both, data science is comprehensive and involves an in-depth understanding of programming languages and machine learning.

Course related to data analytics focuses on data manipulation and data visualization techniques. 

• Google Data Analytics professional certificate

• Course related to Business Analytics 

• PG Diploma in data analytics offered by IIMs.

Obtaining any of these courses will help you learn about tools like Power BI, SQL, Excel, and Tableau.

It is an advanced course and technically advanced course. In the data science-related courses, you will learn programming languages, including core concepts related to machine learning. 

• Data science professional certification

• PG Diploma in Data Science from IIIT

• Machine learning specialization

Obtaining any of the above courses accents your knowledge in real-world application of machine learning, python and R programming language, and TensorFlow.

After completing any of the courses mentioned above, you can avail job roles such as:

• Business intelligence analyst

• Data analyst

• Financial analyst

In the abovementioned roles, you will primarily focus on generating reports, interpreting data, and aiding businesses in making crucial and informed decisions based on historical statistics, data patterns, and trends. These roles are highly dedicated to marketing, operation, and finance.

• Data Engineering

• AI specialist

• ML engineer

• Data scientist

• Working with vast amounts of data to solve complex problems.

• Creating algorithms.

• Predictive modeling in machine learning.

To pursue any of these roles, you must deeply understand programming languages, analytical techniques, and mathematics. 

The global big data analytics market is worth $307.52 billion. A US data analyst can expect to see an entry-level salary range of $37,806 to $75,473 per year.

• According to Market.US, the Data Science Platform Market size will be worth USD 1,826.9 Billion by 2033, from USD 145.4 Billion.

• Growing at a CAGR of 28.8% during the forecast period from 2024 to 2033.

• The estimated total pay for a Data Scientist is $159,480 per year, with an average salary of $114,594 per year. 

• Excel- Data cleaning

• SQL - Querying databases

• Tableau- reporting Insights (Visualization tools)

• Power BI - reporting Insights (Visualization tools)

• Python and R- Programming language

• TensorFlow and Keras -- Models of machine learning

• Apache Spark- Manage large datasets (Big data technologies)

These are the advanced tools for predictive analysis, using algorithms and models to forecast future events and behaviors.

This information will help you make the right decisions in pursuing your career. To learn more about IT- related information, you can stay tuned with Sulekha.