Data Dictionary

Additional Information

Field	Value
Data last updated	September 21, 2024
Metadata last updated	September 21, 2024
Created	September 3, 2024
Format	CSV
License	Open Data Commons Attribution License
Additional info	Data for Ladakh not available on source
Data extraction page	https://nrlm.gov.in/shgReport.do?methodName=showMojorityStateWise
Data insights	The dataset offers a wealth of insights into the operational and demographic characteristics of Self-Help Groups (SHGs). Analyzing the geographic distribution, including state, district, block, Gram Panchayat, and village information, reveals the spatial spread and concentration of SHGs, highlighting regions with varying levels of SHG activity. This can inform targeted support and resource allocation. The formation dates and SHG types enable the tracking of trends over time, shedding light on the growth patterns and focus areas of SHG initiatives. Membership data, including total numbers, gender distribution, and socio-economic classifications such as Scheduled Caste, Scheduled Tribe, and Other Backward Classes, provides a nuanced understanding of the demographic composition and inclusivity of SHGs. Insights into disability status and economic classifications, such as Above Poverty Line (APL), Below Poverty Line (BPL), and Poorest of the Poor, further reveal the socio-economic challenges faced by SHG members. Overall, this dataset facilitates a comprehensive analysis of SHG dynamics, supporting evidence-based policy-making and strategic planning aimed at enhancing the effectiveness and reach of SHG programs.
Data last updated	2,024
Data retreival date	2024-08-18 00:00:00
Datastore active	True
District no	740
Frequency	Other
Gp no	242,220
Granularity	SHG
Has views	True
Id	feef1df7-59c6-43e3-b6ff-3594da5de862
Idp ready	True
Lgd mapping	no
Methodology	Data collection for Self-Help Groups (SHGs) under the National Rural Employment Guarantee Scheme (NRLM) follows a structured methodology to ensure comprehensive and accurate information. The process begins with collecting basic SHG details, including state, district, block, Gram Panchayat, village, SHG name, formation date, type, promotion entity, and bank account information. Essential data points such as meeting frequency, bank linkage, savings per member, and loan account details are recorded. The methodology also involves assessing the preparedness of SHGs through questions about micro planning, basic training, bookkeeping practices, and the identification of a bookkeeper.To support financial inclusion, the data collection framework includes guidelines and multiple handbooks outlining the roles and responsibilities of mission units at various levels. These handbooks provide standardized procedures and best practices for ensuring effective SHG bank linkages and financial management. The collected data is then used to analyze SHG performance and impact, informing strategic decisions and program enhancements.
No indicators	20
Package id	970f9b8f-65bd-4dad-849f-8b57b822c9dd
Position	1
Similar resources	f2196535-38e3-462c-a4c1-2930eb76678f
Size	2.3 GiB
Sku	mord-nrlm_social_category_wise-shg-ot-abc
State	active
States uts no	33
Url type	upload
Years covered	nan
Methodology	Data collection for Self-Help Groups (SHGs) under the National Rural Employment Guarantee Scheme (NRLM) follows a structured methodology to ensure comprehensive and accurate information. The process begins with collecting basic SHG details, including state, district, block, Gram Panchayat, village, SHG name, formation date, type, promotion entity, and bank account information. Essential data points such as meeting frequency, bank linkage, savings per member, and loan account details are recorded. The methodology also involves assessing the preparedness of SHGs through questions about micro planning, basic training, bookkeeping practices, and the identification of a bookkeeper.To support financial inclusion, the data collection framework includes guidelines and multiple handbooks outlining the roles and responsibilities of mission units at various levels. These handbooks provide standardized procedures and best practices for ensuring effective SHG bank linkages and financial management. The collected data is then used to analyze SHG performance and impact, informing strategic decisions and program enhancements.
Indicators	[]
Similar Resources	SHG And Member Profile
Granularity Level	SHG
Data Extraction Page	https://nrlm.gov.in/shgReport.do?methodName=showMojorityStateWise
Data Retreival Date	2024-08-18 00:00:00
Data Last Updated	2024
Sku	mord-nrlm_social_category_wise-shg-ot-abc
Dataset Frequency	Other
Years Covered	nan
No of States/UT(s)	33
No of Districts	740
No of Tehsils/blocks
No of Gram Panchayats	242220
Additional Information	Data for Ladakh not available on source
Number of Indicators	20
Insights from the dataset	The dataset offers a wealth of insights into the operational and demographic characteristics of Self-Help Groups (SHGs). Analyzing the geographic distribution, including state, district, block, Gram Panchayat, and village information, reveals the spatial spread and concentration of SHGs, highlighting regions with varying levels of SHG activity. This can inform targeted support and resource allocation. The formation dates and SHG types enable the tracking of trends over time, shedding light on the growth patterns and focus areas of SHG initiatives. Membership data, including total numbers, gender distribution, and socio-economic classifications such as Scheduled Caste, Scheduled Tribe, and Other Backward Classes, provides a nuanced understanding of the demographic composition and inclusivity of SHGs. Insights into disability status and economic classifications, such as Above Poverty Line (APL), Below Poverty Line (BPL), and Poorest of the Poor, further reveal the socio-economic challenges faced by SHG members. Overall, this dataset facilitates a comprehensive analysis of SHG dynamics, supporting evidence-based policy-making and strategic planning aimed at enhancing the effectiveness and reach of SHG programs.
IDP Ready	Yes
LGD Mapping	No