A very brief introduction to statistics for non-statisticians, with minimal mathematics. Intended audience is people who work with data and analytics.
Presented at Analytics Forward (https://www.meetup.com/Research-Triangle-Analysts/events/237118943/) on 3/10/18
The concept about SAS software and it high end tools.
Stay connected for SAS programming Keywords.
Please not this uploaded ppt is not a copy right of any anonymous,this were created by Sushil Kasar for his basic learnings' and sharing Knowledge activities.
Regards,
Sushil & team.
In this ppt the viewer will able to understand about SAS software. It is a statistical software suite developed by SAS Institute for data management. SAS was developed at North Carolina State University from 1966 until 1976, when SAS Institute was incorporated. SAS was further developed in the 1980s and 1990s with the addition of new statistical procedures, additional components and the introduction of JMP. A point-and-click interface was added in version 9 in 2004. A social media analytics product was added in 2010.
• Portion explained:
• Components of SAS Software
• Origins of SAS Software
• Development of SAS Software
• Recent History of SAS Software
• Software products of SAS Software
• Adoption of SAS Software
• Application of SAS Software
A very brief introduction to statistics for non-statisticians, with minimal mathematics. Intended audience is people who work with data and analytics.
Presented at Analytics Forward (https://www.meetup.com/Research-Triangle-Analysts/events/237118943/) on 3/10/18
The concept about SAS software and it high end tools.
Stay connected for SAS programming Keywords.
Please not this uploaded ppt is not a copy right of any anonymous,this were created by Sushil Kasar for his basic learnings' and sharing Knowledge activities.
Regards,
Sushil & team.
In this ppt the viewer will able to understand about SAS software. It is a statistical software suite developed by SAS Institute for data management. SAS was developed at North Carolina State University from 1966 until 1976, when SAS Institute was incorporated. SAS was further developed in the 1980s and 1990s with the addition of new statistical procedures, additional components and the introduction of JMP. A point-and-click interface was added in version 9 in 2004. A social media analytics product was added in 2010.
• Portion explained:
• Components of SAS Software
• Origins of SAS Software
• Development of SAS Software
• Recent History of SAS Software
• Software products of SAS Software
• Adoption of SAS Software
• Application of SAS Software
Week 4 forecasting - time series - smoothing and decomposition - m.awaluddin.tMaling Senk
Forecasting - time series - smoothing and decomposition methods
Smoothing Method as Moving Averages and exponetial methods. The steps for decomposition methods and example of it. Case study for smothing methods in Single Exponential Smoothing, Double Exponential Smoothing and Triple Exponential Smoothing
Week 4 forecasting - time series - smoothing and decomposition - m.awaluddin.tMaling Senk
Forecasting - time series - smoothing and decomposition methods
Smoothing Method as Moving Averages and exponetial methods. The steps for decomposition methods and example of it. Case study for smothing methods in Single Exponential Smoothing, Double Exponential Smoothing and Triple Exponential Smoothing
This presentations shows how to create a time/date dimension for PowerPivot from the date data in your fact table. I also shows the DAX functions that you can use to add columns to the fact table or a separate dimension table.
Online Statistics Gathering for Bulk Loads - the official name of the feature - was introduced in Oracle 12.1. The idea is to gather optimizer statistics "on the fly" for direct path loads. Sounds good for ETL? In certain scenarios it makes sense but even then there are many points to consider so that it becomes a reliable part of your ETL processes. When exactly will it be working and when not? Do you prevent it yourself? Documented, undocumented cases, known bugs. Which statistics are gathered and which are not? What has to be considered with partitioned tables? Interval partitioning - special case?
Actionable Insights with AI - Snowflake for Data ScienceHarald Erb
Talk @ ScaleUp 360° AI Infrastructures DACH, 2021: Data scientists spend 80% and more of their time searching for and preparing data. This talk explains Snowflake’s Platform capabilities like near-unlimited data storage and instant and near-infinite compute resources and how the platform can be used to seamlessly integrate and support the machine learning libraries and tools data scientists rely on.
How to Integrate OBIEE and Essbase / EPM Suite (OOW 2012)Mark Rittman
Oracle plans to integrate Oracle Essbase and the EPM product suite with Oracle Business Intelligence Enterprise Edition and Oracle Fusion Middleware. So with the latest release of Oracle Business Intelligence Enterprise Edition, 11.1.1.6, how do you connect Oracle Business Intelligence Enterprise Edition to your Oracle Essbase databases and how well does it handle Oracle Essbase features such as scenario and account dimensions, changing outlines, and unbalanced/parent-child hierarchies? How well do Oracle Business Intelligence Enterprise Edition’s ad hoc reporting tools handle Oracle Essbase hierarchies and member selections in the 11.1.1.6 release? Can we still embed Oracle Business Intelligence Enterprise Edition dashboards in Oracle Workspaces? Learn the answers in this session.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
3. INTRODUCTION
EXCEL DASHBOARD
The Excel Dashboard is used to display
overviews of large data tracks. Excel
Dashboards use dashboard elements like
tables and charts to show the overviews.
4. MY DATASET
120 YEARS OF OLYMPICS
HISTORY
The data set used contains information
regarding all the previous Winter and
Summer Olympics.
8. ETL PROCESS
EXTRACT, TRANSFORM, LOAD
EXTRACTING DATA
Downloading Data, Importing Data
TRANSFORMING DATA
Merging Data Sets, Removing
Unwanted Values, Columns
LOADING DATA
Saving Clean Data
9. DASHBOARD
OBJECTIVES
The main aim of the project is to
analyze the Olympics data set to
deduce all the Olympics statistics
which includes the records, facts,
and trends of all the Summer and
Winter Olympics since 1896 with
respect to participants, nations,
and games in various aspects.
10. Item 1 Item 2 Item 3 Item 4 Item 5
40
30
20
10
0
Item 1 Item 2 Item 3 Item 4 Item 5
40
30
20
10
0
Item 1 Item 2 Item 3 Item 4 Item 5
40
30
20
10
0
MAIN OBJECTIVES
FINDING TRENDS AND FIGURES
BY GENDER
Medal Victory, Sports
Participation in terms of
sex.
BY NATIONS
Best Performing Countries,
Year Wise, Male vs
Female, in specific Sports.
BY AGE
Player Participation,
Victory, Male/Female
Ratio with respect to age.
11. This dashboard helps in finding
the required results from the
Olympics data and eases the
decision-making process by
showing the vital parts of the
data.
THE
DASHBOARD
OLYMPICS STATISTICS
15. S W
O T
STRENGTHS
Excellent UI
Easy Navigation
Abstract View
Detailed Analysis
Easy to Understand
WEAKNESSES
Tasks not Achieved due
to (Limited Excel
Features)
OPPORTUNITIES
Work on Weaknesses
Make Dashboard Fit
Screen
THREATS
Lack of Security.
Slow
Occupies large space
16. TOOLS & FEATURES OF EXCEL
MOST USED
Pivot Table Pivot Chart Links
Images &
Icons
VBA
