What is the difference between data analytics and data science? Get Best Data Analyst Certification Course by SLA Consultants India
2025-03-03 Local Events Delhi 69 views Reference: 32
Location: Delhi
Price: Contact us Negotiable
Difference Between Data Analytics and Data Science
Data Analytics and Data Science are two closely related fields, but they serve different purposes and require distinct skill sets. Both fields involve working with data, but their approaches, objectives, and applications vary significantly.
1. Definition
- Data Science: A broad interdisciplinary field that focuses on extracting insights from structured and unstructured data using advanced techniques like machine learning (ML), artificial intelligence (AI), and big data processing.
- Data Analytics: A more focused discipline that deals with analyzing historical data to identify trends, patterns, and business insights, primarily for decision-making and reporting.
2. Scope and Objectives
- Data Science: Aims to build predictive models and AI-driven solutions to forecast future trends. It involves data engineering, machine learning, and deep learning.
- Data Analytics: Focuses on descriptive and diagnostic analytics, answering questions like "What happened?" and "Why did it happen?" using statistical tools and data visualization.
3. Techniques Used
- Data Science: Includes techniques like machine learning, deep learning, artificial intelligence, natural language processing (NLP), and big data analytics.
- Data Analytics: Uses tools such as SQL, Excel, Power BI, Tableau, and statistical analysis for data interpretation and reporting. Data Analyst Course in Delhi.
4. Key Skills Required
- Data Scientists require expertise in Python, R, machine learning algorithms, big data tools (Hadoop, Spark), and cloud computing.
- Data Analysts need strong skills in SQL, Excel, Power BI, Tableau, and statistical analysis to derive business insights.
5. Career Roles and Applications
- Data Science Careers: Data Scientist, Machine Learning Engineer, AI Engineer, Research Scientist.
- Data Analytics Careers: Data Analyst, Business Analyst, Financial Analyst, Marketing Analyst.
6. Industry Applications
- Data Science is used in AI-driven recommendation systems (Netflix, Amazon), fraud detection (banking), and automation (chatbots, robotics).
- Data Analytics is widely applied in business intelligence, market analysis, customer segmentation, and financial reporting.
Conclusion
While data science is a more advanced field involving AI and predictive modeling, data analytics focuses on analyzing past data to drive business decisions. Both fields are highly valuable and offer excellent career opportunities.
Get the Best Data Analyst Certification Course
Master SQL, Python, Power BI, and Data Visualization with SLA Consultants India’s Data Analyst Training Institute in Delhi and start a successful analytics career.
For more details, visit SLA Consultants India today!
SLA Consultants What is the difference between data analytics and data science? Get Best Data Analyst Certification Course by SLA Consultants India details with New Year Offer 2025 are available at the link below:
https://www.slaconsultantsindia.com/institute-for-data-analytics-training-course.aspx
https://slaconsultantsnoida.in/training-institute-advanced-excel-course/
Data Analytics Training in Delhi NCR
Module 1 - Basic and Advanced Excel With Dashboard and Excel Analytics
Module 2 - VBA / Macros - Automation Reporting, User Form and Dashboard
Module 3 - SQL and MS Access - Data Manipulation, Queries, Scripts and Server Connection - MIS and Data Analytics
Module 4 - MS Power BI | Tableau Both BI & Data Visualization
Module 5 - Free Python Data Science | Alteryx/ R Programing
Module 6 - Python Data Science and Machine Learning - 100% Free in Offer - by IIT/NIT Alumni Trainer
Contact Us:
SLA Consultants India
82-83, 3rd Floor, Vijay Block,
Above Titan Eye Shop,
Metro Pillar No. 52,
Laxmi Nagar,New Delhi,110092
Call +91- 8700575874
E-Mail: hr@slaconsultantsindia.com
Website : https://www.slaconsultantsindia.com/
