The document is a project report analyzing literacy trends in India using data from 2015-2016. It introduces planning analytics and IBM Cognos software. The dataset with 616 columns and 38 rows on Indian literacy is described. Criteria for creating cubes and dimensions are discussed. The cleaned dataset is evaluated. Results showing literacy rate trends over time and by state are visualized. The analysis provides insights into progress and gaps in Indian education to help address problems.

1. Project report on
Literacy Trend Analysis
Submitted by: Submitted to: Abhishek Khanna
Name:Bhanu Rathi Roll No.: 19BCS3851
(Designation)
Chandigarh University, Gharuan

2. Certificate
I hereby certify that the work which is being presented in this thesis entitled “Literacy Trend
Analysis”, in partial fulfillment of the requirement for the award of degree of “B.Tech-CSE”
submitted in APEX-CSE, Chandigarh University, Gharuan is an authentic record of my own
work carried based on the extracted dataset from Kaggle dataset through R software. The matter
presented in this report has not been submitted/available online.
Name: Bhanu Rathi
Uid:19BCS3851

3. Acknowledgement
I want to express our special thanks of gratitude to our Planning Analytics in charge Mr.
Abhisekh Khanna for his able guidance and support in completing our project. Along with our
teacher, we would also like to thank IBM for providing us the wonderful and necessary material
required for this project and emerging field of Planning Analytics at last, I would like to thank
Chandigarh University for giving us the platform to learn and present our insights for this
project.
Ghauan
November 2022 Bhanu Rathi

4. Abstract
The given study is an analysis of the Literacy Trends dataset which consists of information of the
trends in various aspects of Indian Education. The given dataset has vast data for years 2015-16
concerning the Indian Literacy and education, which has been divided state wise and further
district wise. We perform analysis on the given dataset and get meaningful insights about the
various trends in Indian education.
In this study we make use of graphs which effectively show us information without having to
read much making it easily understandable. The study isn’t very tech heavy and hence is suitable
for any age group. All the visualizations have been possible because of IBM Cognos as a
platform as it provides all the necessary tools to perform the tasks required. In the end we
conclude our analysis, knowing the fields and areas where the Indian Education lacks behind.

5. List of Tables
Sr. No Caption for table Page No.
1. Metadata
2. Index
3.

6. Table of Contents
Certificate………………………………………………………………………………………….i
Acknowledgement…...……………………………………………………………………………ii
Abstract……………………………………………………………………………………...……iii
List of
Tables...……………………………………………………………………………………iv
1. Introduction to Planning Analytics
2. Introduction to IBM Cognos
3. Introduction to dataset
4. Evaluation criteria for creation of cubes and dimensions
5. Evaluation of dataset
6. Results
7. Conclusion and Future scope

7. Introduction to Planning Analytics
Planning Analytics integrates business planning, performance measurement, and operational data
to enable companies to optimize business effectiveness and customer interaction regardless of
geography or structure. Planning Analytics provides immediate visibility into data,
accountability within a collaborative process and a consistent view of information, allowing
managers to quickly stabilize operational fluctuations and take advantage of new opportunities.
IBM Planning Analytics helps you answer three critical business questions from a single
platform:
 Flexible and timely planning answers "What should we be doing?“
 World-class score carding and dash boarding answers "How are we doing?"
 Accurate reporting and analysis answers "Why are we doing it?"
Use TM1 Architect and TM1 Performance Modeler to build models that use dimensions, cubes,
and rules. You can create applications from cube views, assign workflow, and set up security.
You can then deploy, administer, and maintain your applications. End users have many options
to select from, depending on their requirements. IBM Planning Analytics clients include two
Microsoft Excel offerings: TM1 Perspectives and IBM Planning Analytics for Microsoft Excel.
IBM Planning Analytics Workspace is a Web-based interface that provides you with exciting
ways to plan, create, and analyze your IBM Planning Analytics content. IBM Cognos Insight is a
personal analysis tool that you can use to analyze almost any set of data, including data in your
IBM Planning Analytics system.
Thin clients are TM1 Web and TM1 Application Web. TM1 Performance Modeler, IBM Cognos
Insight, and TM1 Application Web work with the TM1 Applications portal to interact with the
underlying TM1 server. TM1 Operations Console is a Web-based operations tool that is designed
to facilitate the monitoring, support, and management of TM1 servers, providing greater insight
into day-to-day server operations.

8. Introduction to IBM Cognos
A web-based comprehensive business intelligence package from IBM is called Cognos Business
Intelligence. It offers a suite of tools for analytics, scorecarding, reporting, and keeping track of
events and data. The software is made up of a number of parts that are made to satisfy the
various information needs of a business. For example, IBM Cognos Framework Manager, IBM
Cognos Cube Designer, and IBM Cognos Transformer are all parts of IBM Cognos. The
elements described below are web-based components that can be accessed from most popular
browsers
 Cognos Connection-Cognos Connection is the Web portal for IBM Cognos BI. It is the
starting point for access to all functions provided with the suite.
 Query Studio-Query Studio allows simple queries and self-service reports to answer basic
business questions. The report layout can be customized and data can be filtered and
sorted. Formatting and creation of diagrams is also supported
 Report Studio-The Report Studio is used to create management reports
 Analysis Studio-Users can create analyses of large data sources and search for
background information about an event or action
 Event Studio-The Event Studio is a notification tool that informs about events within the
enterprise in real time
 Workspace- It is a web-based interface that allows business users to use existing IBM
Cognos content (report objects) to build interactive workspaces for insight and
collaboration
 Workspace Advanced-It is a web-based interface that allows business users to
author/create reports and analyze information.

9. Introduction to dataset
The Dataset we took is 2015-2016 dataset of our education system from Kaggle which has 616
columns and 38 rows. The Meta data of the dataset is given below:
Field Name Description
statcd State code
ac_year Academic year
statname State name
area_sqkm Area
tot_population Total Population
urban_population Urban Population
grwoth_rate Growth Rate
sexratio Sex Ratio
sc_population % SC Population
st_population % St Population
literacy_rate literacy rate
male_literacy_rate literacy rate- Male
female_literacy_rate literacy rate- Female
distcd Districts: Districts
blkcd Blocks: Blocks
villages Villages: Villages
clusters clusters: clusters
schools schools: schools
sch_1 Number of Schools: Primary with upper primary
and secondary and higher secondary
sch_2 Number of Schools: Upper Primary with secondary
and higher secondary
sch_3 Number of Schools: Primary with upper primary
and secondary
sch_4 Number of Schools: Upper Primary with secondary
sch_5 Number of Schools: Secondary only
sch_6 Number of Schools: Secondary with Hr. Secondary
sch_7 Number of Schools: Hr. Secondary only
sch_r_1 Number of Schools- Rural: Primary with upper

10. primary and secondary and higher secondary
Evaluation criteria for the creation of cubes and dimensions
CUBES
IBM Planning Analytics with Watson stores the data that you need for planning and analysis in
cubes. Each cube typically has a specific purpose. Suppose that you are analyzing sales; you
have a cube that measures the sales for Sedan cars over time. The cube contains three
dimensions: Measures, Product, and Month. Each measure, such as Sales, is organized by a
product and a month. For example, the cell value 300000 represents the sales of Sedan-1 in the
month of January (Jan).
A cube has two or more dimensions. The number of dimensions that there are in a cube depends
on the purpose of a cube. For example, a two-dimensional cube is useful as a lookup table; you
can store exchange rates in a lookup table.
DIMENSIONS
Dimensions are lists of related members. Two or more dimensions are used to make a cube that
can be used for planning and analysis.
Typical dimensions a cube might contain are time, versions, regions, products, departments,
measures. A member is an item in a dimension, so in a time dimension, you can have months,
years, quarters. Each month, year, and quarter is a member. Dimensions can be a simple list with
all members at the same level, or a dimension can be structured with members at different levels
and with multiple hierarchies. How a dimension is structured depends on how you want the data
to be represented.

11. Evaluation of dataset
This dataset was taken considering the need of the analysis as we had to cover as many aspects of factors
affecting literacy as we could. So the dataset is a vast one and consists of 16 columns with 680 rows.
It consists of categorical and continuous values, though the categorical are very less in number i.e. 2 and
rest 14 are continuous. It consists of 6 flag values which are either 0 or 1.
The dataset had to be very clean in order for the analysis to be done successfully and get good results
hence proper cleaning and transformation was done. At the end, there were no missing values making it a
lot easier in the process. Any outlier or missing value would have resulted in absurd outputs which would
have affected the results as a whole.

12. Results

15. Conclusion and Future scope
We have successfully completed the analysis of the Indian Education Dataset and have derived
meaningful insights. Some of these are given below.
Every state has seen an increase in literacy, with some states seeing increases of more than 30%.
States that previously had very high literacy rates are the ones that haven't made any progress.
There are several underlying causes for this pleasing change, including increased awareness
among the socially backward, government policies, general progress, and many others.
India's literacy rate has risen overall, but there is still a long way to go before we can claim to be
a fully literate nation. Similar number of years, and the goal of having a totally literate nation is
not far away.
The results that we get after analysis of this dataset can be used in the future to deal with
problems relating to Indian Education. One can clearly see the fields where we lag behind and
hence start working on it. We cover nearly every aspect of Indian Education and get insights
using visualizations making it easy to understand for any nonprofessional.