data science

Decoding the Key Difference Between Data Science and Data Analytics

Data Science remains a vital force behind advancements across various sectors in the rapidly altering technological landscape. As individuals dive deep into 2024, numerous trends are shaping the trajectory of this dynamic field. One preeminent trend is the rising amalgamation of Machine learning and Artificial Intelligence (AI) into Data Science practices.

Be it big or small, organisations are leveraging high-tech algorithms to derive actionable insights from dynamic datasets, allowing smarter decision-making and enhanced business results. Simply put, in the era of information overload, where every click, search, and transaction generates tremendous amounts of data, the role of data science has become exceptionally crucial.


Are you perplexed between Data Science and Data Analytics?

No worries! 

In this write-up, we will highlight the difference between Data Science and Data Analytics, along with the career opportunities and scope. Below is the difference in the tabular form; read on to continue.

Difference Between Data Science and Data Analytics

FeatureData ScienceData Analytics
Coding LanguagePython is one of the most commonly utilised languages for data science, along with other languages such as C++, Java, Perl, etc.The Knowledge of Python and R Language is imperative for Data Analytics.            
Programming SkillsDeep knowledge of programming is needed for data science. Basic Programming skills are mandatory for data analytics.
Use of Machine LearningData Science utilises machine learning algorithms to get real insights.Data Analytics does not make use of machine learning to get the insight of data.
Required SkillsetData Science uses data mining activities to extract meaningful insights. Hadoop-based analysis is used to derive conclusions from raw data.
Scope  The Data Science scope is large.The scope of Data Analysis is micro (tiny).
GoalsData science deals with explorations and new advancements.Data Analysis utilises existing resources.
Data TypeData Science usually deals with unstructured data.Data Analytics often with structured data.
Statistical SkillsStatistical skills are important in Data Science.The statistical skills are of minimal or no use in data analytics.

Career Opportunities After Data Science and Data Analytics

Oddly enough, pursuing a Data Analytics and Data Science PGDM, or PGDM in Data Science and Business Analytics, opens vast and dynamic job opportunities for brilliant minds. Here are some of the potential career paths you can contemplate. 

  • Data Scientist
  • Data Analyst
  • Business Intelligence (BI) Analyst
  • Machine Learning Engineer
  • Data Engineer
  • Quantitative Analyst
  • Big Data Engineer
  • Consultant in Data Science and Analytics
  • Research Scientist (in academia or industry)
  • Entrepreneur/Start-up Founder

And more!

The demand for well-versed professionals in Data Science and Business Analytics is continuously soaring across numerous sectors, which incorporates finance, healthcare, e-commerce, technology, and more. Constant learning and staying updated with advancing technologies are crucial for a successful and satisfying career in this field.

Decipher the Data Code with PGDM in Data Science and Business Analytics at the International School of Business & Research (ISBR)

Nestled in the heart of Bangalore, the International School of Business & Research (ISBR) provides an all-encompassing Postgraduate Diploma in Data Science and Business Analytics, meticulously curated to furnish students with the imperative skill sets and in-depth knowledge needed to excel in the swiftly expanding data science sphere.

The two-year programme is geared towards preparing students for vast and varied career paths in data/business analysis, such as data scientists, business analysts, data analysts, and so on. 

This holistic industry-oriented curriculum spans a broad spectrum of data science topics and is carefully crafted to be hands-on and pragmatic, focusing on the practical application of data science techniques in real-world scenarios. The coursework covers subjects such as:

  • Data Analysis
  • Statistics
  • Machine Learning
  • Data Visualization

And more!

A distinct feature of the PGDM in Data Science and Business Analytics is its real-world data science projects, affording students valuable practical experience and the opportunity to construct a vigorous portfolio. The programme further enriches the learning experience via guest lectures and industry visits, promoting connections with seasoned data science and business analytics professionals.

The dedicated faculty members at ISBR, possessing substantial expertise in data science and related domains, play a great role in imparting knowledge. Typically dedicated to delivering high-quality education, they equip students with the skills and insights that are highly essential for success in the dynamic Data Science industry.

Crack the Code to Data Brilliance

Undeniably, the Data Sciences landscape is encountering a convergence of AI, ethical considerations, skill development, and edge computing. As we steer the data-driven future, staying abreast of these trends will be fundamental for individuals and organisations alike. If you think you have skills to extract data and are willing to nurture it to another level, pursue a PGDM course in Data Science and Business Analytics International School of Business & Research, aka ISBR.


Which is better data science or data analytics?

Both data science and data analytics are valuable fields, but they serve different purposes. Data science involves complex algorithms and predictive modelling to gain insights and make informed decisions. Data analytics focuses on analysing historical data to identify trends and patterns for business intelligence.

Does data analytics require coding?

Yes, data analytics often requires coding, as proficiency in languages like Python, R, or SQL is commonly used for data manipulation, analysis, and visualisation.

What is the scope of PG Diploma in data science?

The scope of a PG Diploma in Data Science is extensive, encompassing roles in data analysis, machine learning, and artificial intelligence across various industries. Graduates can pursue careers as data scientists, analysts, and AI specialists, addressing the growing demand for skilled professionals in the data-driven landscape.

Is PG Diploma in data science worth it?

Yes, a PG Diploma in Data Science is worth it, as it provides specialised knowledge and skills sought after in the growing field of data science, enhancing career opportunities.