analysis data

1. Online Analytical Processing
Submitted to: Submitted by:
Dr. Shelja Ganesh Sakshi
2220065
BCA-4th
Sem(S1)

2. CONTENTS
 History
 Introduction
 Types of OLAP
 Working of OLAP
 Key Features of OLAP
 Future Scope
 Applications of OLAP
 Advantages & Disadvantages
 Conclusion

3. History
1990s: OLAP, as a term, gained popularity in the early to mid-
1990s. It was coined by Dr. Edgar F.Codd, a computer scientist
known for his work on relational databases.
OLAP systems were designed to facilitate interactive analysis of
multidimensional data from different perspectives.

4. Introduction
Online analytical processing (OLAP) software executes detailed
analysis on massive volumes of business data, drawn from
sources such as data lakes or deep storage.
End users, such as analysts, executives, and engineers, use
OLAP platforms to dissect data around operational performance
and profitability, access critical business insights or product
strategy.

5. Types of OLAP
 Multidimensional OLAP(MOLAP):
 In MOLAP systems, data is stored in a multidimensional array
(or cube) format.
 MOLAP systems are optimized for fast query performance
and are well-suited for scenarios where response time is
critical.

6.  Relational OLAP(ROLAP):
 ROLAP systems store data in a relational database
management system (RDBMS), such as Oracle, SQL Server,
or MySQL.
 Instead of pre-aggregating data into a multidimensional cube,
ROLAP systems perform OLAP operations directly on
relational tables.

7.  Hybrid OLAP (HOLAP):
 HOLAP systems combine elements of both MOLAP and
ROLAP approaches.
 They store summary data (aggregates) in a multidimensional
format for fast query performance, while detailed data is
stored in a relational database for flexibility.
 Real-Time OLAP(ROLAP):
 Real-Time OLAP (RTOLAP) systems focus on providing real-time
or near-real-time access to operational data for analysis.
 These systems are designed to handle continuous streams of data
and support ad-hoc queries with minimal latency.

8. Working
Here's how OLAP typically works:-
 Data Acquisition
 Dimensional Modeling
 Data Cubes
 OLAP Operations
 Query and Analysis
 Aggregation and Calculations
 Result Presentation
 Performance Optimization

9. Key Features of OLAP

10. Future Scope
Future Scope of OLAP :-
 Big data Integration
 Cloud Based OLAP
 AI And Machine Learning Integration
 Enhanced visualization and

11. Applications of OLAP
Some common applications of OLAP include:
 Business Intelligence(BI)
 Financial Analysis and Planning
 Sales And Market Analytics
 Customer Relationship Management(CRM)

12. Advantages of OLAP
Some key advantages of OLAP include:
 Multidimensional Analysis
 Fast Query Performance
 Aggregation and Drill Down
 Hierarchical Navigation
 Data Visualization

13. Disadvantages of OLAP
Some of the key disadvantages of OLAP include:
 Complexity of Implementation
 Data Latency
 Storage Requirements:
 Limited Detailed Level
 Performance Degradation With Complex Queries

14. Conclusion
OLAP systems allows flexible and dynamic questions to be
asked of big data. By combining OLAP with multicriteria
decision-making techniques, we can allow business executives
to incorporate insights from real-world data into the systematic
evaluation of different business options

15. THANKYOU