Data Analytics
(JNTUH)
UNIT - I Data Management: (UNIT-1 PDF)
1.1 Design Data Architecture
1.2 Understand various sources of Data
1.3 Data Quality
1.4 Preprocessing
UNIT - II Data Analytics: (UNIT-2 PDF)
2.1 Introduction to Analytics
2.2 Introduction to Tools and Environment
2.3 Application of Modeling in Business
2.4 Databases & Types of Data and variables
2.5 Data Modeling Techniques Overview
2.6 Missing Imputations
3.2 Blue property assumptions
3.3 Least Square Estimation
Logistic Regression:
3.5 Model Theory
3.6 Model fit Statistics
3.7 Model Construction
3.8 Analytics applications to various Business Domains etc.
UNIT-IV (UNIT-4 PDF)
Object Segmentation:
4.1 Regression Vs Segmentation
4.2 Supervised and Unsupervised Learning
4.3 Tree Building
Time Series Methods:
4.4 Arima
4.5 Measures of Forecast Accuracy
4.5 Measures of Forecast Accuracy (Another version)
4.6 ETL approach
UNIT - V Data Visualization: (UNIT-5 PDF)
5.1 Pixel-Oriented Visualization Techniques
5.2 Geometric Projection Visualization Techniques
5.3 Icon-Based Visualization Techniques
5.4 Hierarchical Visualization Techniques
5.5 Visualizing Complex Data and Relations
PPT UNIT V - another version
(JNTUH)
UNIT - I Data Management: (UNIT-1 PDF)
1.1 Design Data Architecture
1.2 Understand various sources of Data
1.3 Data Quality
1.4 Preprocessing
UNIT - II Data Analytics: (UNIT-2 PDF)
2.1 Introduction to Analytics
2.2 Introduction to Tools and Environment
2.3 Application of Modeling in Business
2.4 Databases & Types of Data and variables
2.5 Data Modeling Techniques Overview
2.6 Missing Imputations
UNIT - III: (UNIT-3 PDF)
Regression:
3.1 Concepts3.2 Blue property assumptions
3.3 Least Square Estimation
Logistic Regression:
3.5 Model Theory
3.6 Model fit Statistics
3.7 Model Construction
3.8 Analytics applications to various Business Domains etc.
UNIT-IV (UNIT-4 PDF)
Object Segmentation:
4.1 Regression Vs Segmentation
4.2 Supervised and Unsupervised Learning
4.3 Tree Building
Time Series Methods:
4.4 Arima
4.5 Measures of Forecast Accuracy
4.5 Measures of Forecast Accuracy (Another version)
4.6 ETL approach
UNIT - V Data Visualization: (UNIT-5 PDF)
5.1 Pixel-Oriented Visualization Techniques
5.2 Geometric Projection Visualization Techniques
5.3 Icon-Based Visualization Techniques
5.4 Hierarchical Visualization Techniques
5.5 Visualizing Complex Data and Relations
PPT UNIT V - another version
Data Analytics is an essential asset for all businesses. Clients can use data analytics to analyze business activities.
ReplyDeleteThank you, I’ve just been searching for information about this topic for a while and yours is the greatest I’ve discovered till now. But, what in regards to the conclusion? Are you sure concerning the supply? os path
ReplyDelete