Sas For Finance Pdf: Fill & Download for Free

For More Details Please Contact LEARNCHASEIntroduction to SASIntroduction to Base SAS, Installation of SAS tool, Getting started with SAS, various SAS Windows – Log, Explorer, Output, Search, Editor, etc. working with data sets, overview of SAS Functions, Library Types and programming filesSAS Enterprise GuideImport/Export Raw Data files, reading and sub setting the data set, various statements like WHERE, SET, MergeHands-on Exercise – Import Excel file in workspace, Read data, Export the workspace to save dataSAS Operators & FunctionsVarious SAS Operators – Arithmetic, Logical, Comparison, various SAS Functions – NUMERIC, CHARACTER, IS NULL, CONTAINS, LIKE, Input/Put, Date/Time, Conditional Statements (Do While, Do Until, If, Else)Hands-on Exercise – Apply logical, arithmetic operators and SAS functions to perform operationsCompilation & ExecutionUnderstanding about Input Buffer, PDV (Backend), learning what is MissoverUsing VariablesDefining and Using KEEP and DROP statements, apply these statements, Format and Labels in SAS.Hands-on Exercise – Use KEEP and DROP statementsCreation and Compilation of SAS Data setsUnderstanding Delimiter, dataline rules, DLM, Delimiter DSD, raw data files and execution, list input for standard data.Hands-on Exercise – Use delimiter rules on raw data filesSAS ProceduresThe various SAS standard Procedures built-in for popular programs – PROC SORT, PROC FREQ, PROC SUMMARY, PROC RANK, PROC EXPORT, PROC DATASET, PROC TRANSPOSE, , PROC CORR etc.Hands-on Exercise – Use SORT, FREQ, SUMMARY, EXPORT and other proceduresInput statement and formatted inputReading standard and non-standard numeric inputs with Formatted inputs, Column Pointer Controls, Controlling while a record loads, Line pointer control / Absolute line pointer control, Single Trailing , Multiple IN and OUT statements, DATA LINES statement and rules, List Input Method, comparing Single Trailing and Double Trailing.Hands-on Exercise – Read standard and non-standard numeric inputs with Formatted inputs, Control while a record loads, Control a Line pointer, Write Multiple IN and OUT statementsSAS FORMATSAS FORMAT statements – standard and user-written, associating a format with a variable, working with SAS FORMAT, deploying it on PROC Data sets, comparing ATTRIB and FORMAT statements.Hands-on Exercise – Format a variable, deploy format rule on PROC DATA set, Use ATTRIB statementSAS GraphsUnderstanding PROC GCHART, various Graphs, Bar Charts – Pie, Bar, 3D, plotting variables with PROC GPLOT.Hands-on Exercise – Plot graphs using PROC GPLOT Display charts using PROC GCHARTInteractive Data ProcessingSAS advanced data discovery and visualization, point-and-click analytics capabilities, powerful reporting tools.Data Transformation FunctionCharacter Functions, Numeric Functions, Converting Variable Type.Hands-on Exercise – Use Functions in data transformationOutput Delivery System (ODS)Introduction to ODS, Data Optimization, How to generate files (rtf, pdf, html, doc) using SASHands-on Exercise – Optimize data, generate rtf, pdf, html and doc filesSAS MACROSMacro Syntax, Macro Variables, Positional Parameters in a Macro, Macro StepHands-on Exercise – Write a macro, Use positional parametersPROC SQLSQL Statements in SAS, SELECT, CASE, JOIN, UNION, Sorting DataHands-on Exercise – Create sql query to select and add a conditionUse a CASE in select queryAdvanced Base SASBase SAS web-based interface and ready-to-use programs, advanced data manipulation, storage and retrieval, descriptive statistics.Hands-on Exercise – Use web UI to do statistical operationsSummarization ReportsReport Enhancement, Global Statements, User-defined Formats, PROC SORT, ODS Destinations, ODS Listing, PROC FREQ, PROC Means, PROC UNIVARIATE, PROC REPORT, PROC PRINTHands-on Exercise – Use PROC SORT to sort the results, List ODS, Find mean using PROC Means, print using PROC PRINTSAS ProjectsProject 1 – Categorization of patients based on count of drugs for their therapyDomain: Health CareObjective – This project aims to find out descriptive statistics & subset for specific clinical data problems. It will give them brief insight about BASE SAS procedures and data steps.Problem Statement :Count the number of patients and list of those patientsWho were ever on at least one of the four drugsWho were ever on each of the four drugsWho had never been on any drugOutput should be four datasetsTYPA – Contains the list of patients from problem 1TYPB – Contains the list of patients from problem 2TYPC – Contains the list of patients from problem 3SUMMARY – – Contains the summary of counts for each of 3 problemsProject 2 – Build revenue projections reportsDomain: SalesObjective – This project will give you hands-on experience in working with the SAS data analytics and business intelligence tool. You will be working on the data entered in a business enterprise setup, aggregate, retrieve and manage that data. You will learn to create insightful reports and graphs and come up with statistical and mathematical analysis to scientifically predict the revenue projection for a particular future time frame. Upon completion of the project you will be well-versed in the practical aspects of data analytics, predictive modeling, and data mining.Project 3 :- Impact of pre-paid plans on the preferences of investorsDomain: Finance MarketObjective – The project aims to find the most impacting factors in preferences of pre-paid model, also identifies which are all the variables highly correlated with impacting factorsProblem Statement :To identify the various reasons for Pre-paid model preference and non-preference among the investors. And also understand the penetration of the Pre-paid model in the brokerage firmsTo identify the Pre-paid scheme advantages and disadvantages and also identify brand wise market shareIn addition to this, the project also looks to identify various insights that would help a newly established brand to foray deeper into the market on a large scaleProject 4 :- k-Means Cluster analysis on Iris datasetDomain: AnalyticsObjective – k-Means Cluster analysis on Iris dataset to predict about the class of a flower using its petal’s dimensionsRequirements :-Using the famous Iris dataset, predict the class of a flowerPerform k-means cluster analysisPlease Contact LEARNCHASE

A story will answer your question! At least, I hope so.Before getting in a famous Central Bank (I would not say the “brand” I am not here to advertising my cv) I spent six months in front of a Treasury Desk. It was the 2015.Financial providers are the wayYou know that period of in time, you had to inform your boss by mail that you just closed the order in the market and you dealt with it by getting a good price? It was already over in the 2015. If you can use Financial providers, you may be focused on finance side and leave many routinely task such as send an email cointaining the ticket of my order to the “machine”.So, the capatility to work while interacting with such providers was and it is still high valuable skillAnalytics is on the riseAre you in a job providing slides, written procedures and documents or checking for errors (e.g internal audit)? In that case, my view is very pessimistic. This job are being automatized. In a Central Bank, I spent two years to automatize those tasks in SQL and SAS. Now, the employees of that office have to click some buttons as a daily task.The capability to produce interesting dossiers and reports by enquiring data with SAS, SQL in order to process those data maybe throughout Tableau is actually one of the HOTTest skill that you may have!Summing up, all roles related to:check for dataproduce a pdf or power point reportmake slides or report more pretty “by hand”ctrl+c + ctrl+v roles in many Legal officesinternal control in Banksdata entrysales who does not even know what is the C++ or the SQLaccountantAll the roles above will die in the near futureAt end, this is my own personal opinion! Take it seriously but not to much. Things can change!

This one is rather easy to google, but I did it for you this time. :)I am quoting this from a google search “procurement analytics pdf” (which side-note, adding pdf to searches (can) pull up great content. The information is from an AT Kearny document called “Boost Procurements Buying Power with Analytics” written in 2014 available for free, which I have made a link to by clicking on the title.“Today, 67 percent of companies of various sizes and in many industries rely on analytics to gain competitive advantage. That’s an 80 percent increase over just two years ago, according to a survey conducted by the MIT Sloan Management Review and SAS Institute. The number will continue to grow as companies understand analytics’ capabilities and excel at its use.Many organizations have move from using analytics in isolated departments and without clear purpose to applying it across the enterprise to meet specific objectives. With procurement, it used to be enough ot identify high-quality, competitively priced suppliers. But as CEOs push this function to be more strategic, it is now involved in several areas:Innovation. Analytics can provide new solutions o its own or support R&D with sources for new products or services to advance offerings.Risk Management. Supply risk can be woven into the sourcing equation to ensure business continuity.Sustainability, diversity, and social responsibility. All newer factors can be monitored by many stakeholders.Collaboration. Analytics can support the needs and objectives of myriad functions. For example, marketing may require frequent artwork changes, while finance expects 40-day payment terms. R&D may need suppliers to test new items following a protocol, and engineering could need help qualifying new vendors.This added complexity complicates award decisions. Data must be reliable, yet many procurement groups still use qualitative information and outdated forecasts. Analytics can help procurement own the details, but a little self-analysis is needed first.”Hope this answers your question, and be sure to check out the rest of this pdf. It’s filled with great directional information, as well as their numerous other white-papers and research. A special thanks to ATKearney