overviews on the concept of statistical system, its definition, components, role and future developments, migrating from classical design to a modern one, integrated, and efficient, and highly responsive to new demands.
Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns
Topics for the class include multiple regression, dummy variables, interaction effects, hypothesis tests, and model diagnostics. Prerequisites include a general familiarity with Stata, including importing and managing datasets and data exploration, the linear regression model, and the ordinary least squares estimation.
Workshop materials including do files and example data sets are available from http://projects.iq.harvard.edu/rtc/event/regression-stata
Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns
Topics for the class include multiple regression, dummy variables, interaction effects, hypothesis tests, and model diagnostics. Prerequisites include a general familiarity with Stata, including importing and managing datasets and data exploration, the linear regression model, and the ordinary least squares estimation.
Workshop materials including do files and example data sets are available from http://projects.iq.harvard.edu/rtc/event/regression-stata
Data warehousing Demo PPTS | Over View | Introduction Kernel Training
Module 1:
Introduction to Data Warehouse & Business Intelligence
Module 2: Data Warehouse Architecture
Module 3: Warehouse: D & F – Dimension & Fact Tables
Module 4: Data Modeling
Module 5: Building Data Warehouse with ER Win
Module 6: Introduction to Open Source ETL Tool – Talend DI Open Studio 5.x
Module 7: Building ETL Project with Talend DI Open Studio 5.x
Module 8: Introduction to Data Visualization BI Tool – Tableau 9.x
Module 9: Building Data Visualization BI Project With Tableau 9.x
Module 10: An Integrated Data Ware Housing & BI Project
Which Case-Studies will be a part of data warehousing and business intelligence online training?
Learn Data warehousing and business intelligence online training by real time expert. Be a part of live sessions. Data warehousing and business intelligence classes by Expert.
A strong relationship with the founder
of Data Vault for over 3 years now.
Supporting your business with 40+
certified consultants.
Incorporated as the preferred
Enterprise Data Warehouse modelling
paradigm in the Logica BI Framework.
Satisfied customers in many countries
and industry sectors
What is knowledge management System?
History of knowledge management system.
Knowledge Management Life-cycle.
Scope of knowledge management.
The Different Types of Knowledge.
Knowledge Management Framework.
Benefits of a Knowledge management System within an Organization.
Technologies for Knowledge Management.
Knowledge Management Value chain.
Knowledge Networking System.
MIS
In any single written message, one can count letters, words or sentences. One can categories phrases, describe the logical structure of expressions, ascertain associations, connotations, denotations, elocutionary forces, and one can also offer psychiatric, sociological, or political interpretations. All of these may be simultaneously valid. In short a message may convey a multitude of contents even to a single receiver.
Learn how to navigate Stata’s graphical user interface, create log files, and import data from a variety of software packages. Includes tips for getting started with Stata including the creation and organization of do-files, examining descriptive statistics, and managing data and value labels. This workshop is designed for individuals who have little or no experience using Stata software.
Full workshop materials including example data sets and .do file are available at http://projects.iq.harvard.edu/rtc/event/introduction-stata
Summary about official statistics and future development, covering the components, topics in official statistics, data sources, and the changes due to big data revolution.
Data warehousing Demo PPTS | Over View | Introduction Kernel Training
Module 1:
Introduction to Data Warehouse & Business Intelligence
Module 2: Data Warehouse Architecture
Module 3: Warehouse: D & F – Dimension & Fact Tables
Module 4: Data Modeling
Module 5: Building Data Warehouse with ER Win
Module 6: Introduction to Open Source ETL Tool – Talend DI Open Studio 5.x
Module 7: Building ETL Project with Talend DI Open Studio 5.x
Module 8: Introduction to Data Visualization BI Tool – Tableau 9.x
Module 9: Building Data Visualization BI Project With Tableau 9.x
Module 10: An Integrated Data Ware Housing & BI Project
Which Case-Studies will be a part of data warehousing and business intelligence online training?
Learn Data warehousing and business intelligence online training by real time expert. Be a part of live sessions. Data warehousing and business intelligence classes by Expert.
A strong relationship with the founder
of Data Vault for over 3 years now.
Supporting your business with 40+
certified consultants.
Incorporated as the preferred
Enterprise Data Warehouse modelling
paradigm in the Logica BI Framework.
Satisfied customers in many countries
and industry sectors
What is knowledge management System?
History of knowledge management system.
Knowledge Management Life-cycle.
Scope of knowledge management.
The Different Types of Knowledge.
Knowledge Management Framework.
Benefits of a Knowledge management System within an Organization.
Technologies for Knowledge Management.
Knowledge Management Value chain.
Knowledge Networking System.
MIS
In any single written message, one can count letters, words or sentences. One can categories phrases, describe the logical structure of expressions, ascertain associations, connotations, denotations, elocutionary forces, and one can also offer psychiatric, sociological, or political interpretations. All of these may be simultaneously valid. In short a message may convey a multitude of contents even to a single receiver.
Learn how to navigate Stata’s graphical user interface, create log files, and import data from a variety of software packages. Includes tips for getting started with Stata including the creation and organization of do-files, examining descriptive statistics, and managing data and value labels. This workshop is designed for individuals who have little or no experience using Stata software.
Full workshop materials including example data sets and .do file are available at http://projects.iq.harvard.edu/rtc/event/introduction-stata
Summary about official statistics and future development, covering the components, topics in official statistics, data sources, and the changes due to big data revolution.
Presentation by Peter Vagi at the Seminar on Monitoring and Evaluation for representatives of the Turkish Prime Ministry, taking place in Kizilcahamam, Republic of Turkey, 4-5 May 2017 [English].
overview on the new generation of official statistics, with focus on the automated and computerized statistical process as integrated and generalized model, as a base for a modern statistical organization.
beside the role of IT component in developing smart statistics, and the impact in improving the timing and quality and responsiveness of the statistical organization.
OECD Principles on Budgetary Governance - Anne Keller, OECDOECD Governance
This presentation was made by Anne Keller, OECD, at the 40th Annual Meeting of OECD Senior Budget Officials (SBO) held in Tallinn, Estonia, on 5-6 June 2019
HLEG thematic workshop on Measurement of Well Being and Development in Africa...StatsCommunications
HLEG thematic workshop on Measurement of Well Being and Development in Africa, 12-14 November 2015, Durban, South Africa, More information at: www.oecd.org/statistics/measuring-economic-social-progress
Tuesday 28 June, W3 - Sector self regulation and improvement - George Garlick lgconf11
This session will focus on the early lessons emerging from the implementation of the sector owned approach to self regulation and improvement – with a particular emphasis on the practicalities and benefits to be gained from sharing and comparing key performance data and the contribution peer challenge and support can make to improvement, in this case in regard to children’s services.
Speakers:
David Simmonds, London Borough of Hillingdon
George Garlick, Chief Executive, Durham County Council
Janette Karklins, Director of Children’s Services, Bracknell Forest Council
Chair: Cllr Jill Shortland, Vice Chair, Improvement Programme Board, LG Group
Overview of the new CountrySTAT system and strategyFAO
"http://www.countrystat.org/ The new CountrySTAT aims at strengthening or at seeking collaboration and synergies with agencies and international initiatives, such as AMIS, UNECA, IFAD, SADC, IMF, etc. on different areas such as sharing of data, assistance at the country level, methodological improvements, etc.
"
This lecture will analyze the increasingly important topic of assessment and evaluation in e-government. Different models, methodologies and approaches will be presented.
Dimitris Sarantis, Researcher, United Nations University, PT
Open Government Data: What it is, Where it is Going, and the Opportunities fo...OECD Governance
Keynote presentation given by Ryan Androsoff (Digital Government Policy Analyst, OECD) at the 2015 EUROSAI-OLACEFS conference in Quito, Ecuador on 25 June 2015. Focus of the presentation is on Open Government Data and the opportunities for Supreme Audit Institutions presented by open data. Video of the presentation is available at: https://youtu.be/SlBfxmecJhI?t=1h50m19s
For more information on OECD's work relating to Open Government Data please see: http://www.oecd.org/gov/public-innovation/open-government-data.htm
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
2. Presentation Route Map
Overview.
Role of FCSA in NSS
Types of Statistical System.
Strengthening NSS (Things to do).
Conclusions
3. 3
SAMPLE TITLE
What are official statistics?
Official statistics are all statistics produced by
government departments and specified
according to UAE related laws (Federal and Local
level).
UN standards:
The United Nations Fundamental Principles of
Official Statistics provides the basic framework
for official statistics in member countries.
4. 4
SAMPLE TITLE
Determinants of official statistics
• Not all statistics are defined as Official
• Statistics are defined as Official if they are:
1. Produced by the government/ related entity
2. sustainable
3. relevant, and,
4. meet certain quality standards
6. 6
SAMPLE TITLE
Official Statistics are used for a variety of purposes:
• Measure population characteristics,
environmental issues, the pulse of the economy
thus allowing one to make comparisons with the
past, with other countries and set benchmarks for
the future. They provide a meaningful description
of the society and development.
• Facilitate the decision making processes of
businesses and individuals. Businesses make
investment and employment decisions on the
basis of Official Statistics. They support decision
making processes by the wider community.
7. 7
SAMPLE TITLE
Official Statistics are used for a variety of
purposes:
• Policy formulation, implementation and
evaluation by the Government
• Resource allocation and targeting – statistics
helps in identifying people and regions in need
and allow authorities to make and implement
timely interventions.
8. 8
SAMPLE TITLE
What is the Official Statistics System?
“The government-wide system of policies,
practices, processes, underlying data sources,
and people that are involved in producing and
disseminating official statistics”.
9. 9
A system is defined by the elements constituting it
The nature of the system is defined by the relations
between these elements
The core statistical systems consist of all the
statistics producing entities (independent units)
The wider system also includes the data providers
and the users
10. 10
SAMPLE TITLE
In collaborative systems the elements work
together on the basis of consensus and equal
basis.
In a hierarchical system one organization basically
sets most of the rules
Most statistical systems are a mixture of these
two types
11. 11
SAMPLE TITLE
National Statistical systems can be:
• Part of central government
• Organization varies, but even when
centralized may involve several agencies
National Statistical System have a dual role:
• To serve the needs of government
• To provide information to the public
12. 12
SAMPLE TITLE
In general the structure includes:
1. National Statistical Agency.
2. Line ministries.
3. Regional and local offices..
13. 13
SAMPLE TITLE
• No statistical system is entirely centralized or
decentralized (international experience).
• In the broad spectrum from ‘totally centralized’
to ‘totally decentralized’, some statistical
organizations may find themselves either near
the centralized end (Canada, Netherlands,
Australia), or near the decentralized end (USA,
Japan).
• But many are somewhere in between in
between.
14. 14
SAMPLE TITLE
• Even in highly centralized statistical systems
the Central Bank and line ministries usually
play some role in the production of official
statistics.
• However, many statistical systems are highly
dominated by a ‘single institution’. Driver
or the Heart of the system!
15. 15
SAMPLE TITLE
‘SINGLE INSTITUTION STATISTICAL SYSTEM’
‘A system with one department within the
Government to organize and operate a scheme of
coordinated social and economic statistics
pertaining to the whole country.
This department collects, compiles and publishes
statistical information and, in addition,
collaborates with other departments of
Government in the compilation of administrative
and specialized statistics’.
16. 16
SAMPLE TITLE
There are several types of decentralized SS:
• A statistical system decentralized by subject,
with a coordination authority.
• A statistical system decentralized by subject
with no central control or coordination.
• A statistical system decentralized by subject
with minimal control or coordination.
19. Phase 1
Common
needs
assessment
Phase 2
Common
design
Phase 3
Common
build
Phase 4
Common
collection
Phase 5
Common
processing
Phase 6
Common
analysis
Phase 7
Common
dissemination
Phase 8
Common
evaluation
Input data
Input data
Disseminated
data
21. 21
• Its some how as “ Statistical industrialization”
• A response to strategic challenges and
opportunities due to:
1. Data deluge: Big Data, open data ….
2. Competition: NSOs are not the only players
in the market!
3. Changing needs and rising expectations
from users.
4. Government expect efficiency (“do more
with less”)
22. Institutional arrangements; Partners & stakeholders
Institutional
setting
Management and internal policy (roles and responsibilities map)
Information, Communication Technology (ICT) (connectivity)
Standards and methods
Statistical
infrastructure
Data collection
Data processing
Data integration
Registers, frames Surveys
Inputs
FromPartners
Integrated
Statistics, accounts
Household and
demographic
statistics
Economic &
environmental
statisticsOutputs/
Dissemination
Statistical
operations
24. 24
Improving Institutional Coordination:
• Enhancing the integration and access to data
between NSS components and partners,
• Strengthening the information system and
institutional framework to support a modern
and efficient statistical system; SDMX, GDDS,
Open data, NSDP, DATA ATLAS
• Start, work, and improve by cooperation
25. 25
Improving Operational Level of NSS:
• Developing an efficient information
management system.
• Development and Implementation of an
operational framework (FEDNET, STAT NET …;
• Incorporating Big Data and Open Data
initiatives as a new developments in statistical
and information new age.
26. 26
Modernization of Organizational Modules:
• Strengthening the statistical capacity of the NS
components on the national level.
• Reinforce its role on the regional and
international level by joining experts groups.
• Strengthening the Legal framework to insure the
access, use and reuse of data, and maintain the
confidentiality and data security.
27. 27
Finally;
If we succeed in meeting the mentioned homework
We may be ready to initiate an orchestrated
Modernized system
29. 29
SAMPLE TITLE
A basic framework for the initiating and organizing
statistical organizations is defined in:
UN Manual for organizing statistical offices version 4
Disseminated in 2004 by UNSD
The Fundamental Principles of Official Statistics
(adopted by the United Nations Statistical Commission in
April 1994); and
The Principles Governing International Statistical
Activities
(endorsed by the Committee for Coordination of
Statistical Activities in September 2005).
30. 30
SAMPLE TITLE
Information on National Statistical Systems
http://unstats.un.org/unsd/methods/inter-
natlinks/sd_natstat.asp
How the National Statistics System Impacts on Service Delivery, Service Delivery Review,
Volume 1, No 3, 2002. South Africa
http://www.dpsa.gov.za/documents/service_delivery_review/vol1no3/how%20the
%20national%20statistics%20system%20impacts%20on%20service%20delivery.pdf
Paris21: Why Governments need good statistics?
http://www.paris21.org/documents/why-governments-need-good-statistics.pdf
National Strategies for the Development of Statistics and their Expected Impact on
Agricultural and Rural Statistics. Mr. Graham Eele, World Bank, United Kingdom
http://www.nass.usda.gov/mexsai/Papers/strategiesp.doc
National Strategy for the Development of Statistics, Paris21, Documents and Knowledge
base
http://www.paris21.org/pages/designing-nsds/NSDS-documents-knowledge-
base/index.asp?orderby=e&orderin=1&tab=KnowledgeBase&option=doc