Welcome to the module of SAS base and advanced!
• SAS or Statistical Analysis System, is a software suite developed by SAS Institute for advanced analytics, multivariate analyses, business intelligence, data management, and predictive analytics.
• 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.
• It enables us to perform the following tasks :-
i) Data Entry, Retrieval and Management
ii) Report Writing and Graphics Design
iii) Business Forecasting and Decision Support
iv) Operations Research and Project Management
v) Applications Development
• Companies which use SAS include
iii) Tata Consultancy Services
vi) Facebook, etc
• SAS, today, is the most widely used Business Intelligence Software. There are other software in the market like EXCEL, BUSINESS OBJECT(BO),ORACLE,COGNOS etc., but there are a number of reasons why SAS is preferred over all the others.
• It is an ETL (Extraction, Transformation and Loading) tool. The data (in raw format) extracted from its storage location and then ‘Transformation‘ of the data takes place. Transformation can pertain to treatment of missing values (e.g. putting ‘0‘ or ‘NA‘) when an observation is missing and all sorts of data manipulation can be done here. The data (after cleaning) can be finally loaded to the data warehouse.
Hence at a glance, SAS is capable of performing the following tasks:
• SAS can fetch/access data from a lot of sources including: Oracle, Excel, Raw Databases and SAS files
• SAS Data management capabilities include: Subsetting Data, Creating new variables and Cleaning and Validating Data
• We can rely on SAS for a lot of statistical analysis of big data, starting from basic calculation of descriptive statistics (mean, median, mode) to complex topics including Prediction and Forecasting
• Data presentation is extremely advanced in SAS. There are a lot of data presentation tools available in this software. We can create different reports also in SAS: List reports, summary reports, graph reports and print reports being the majorly used ones.
• SAS can also collate the datasets using a common characteristic , say, Customer ID and it can also merge or append data sets. For example, there is one dataset on Customer ID, Age , Gender and Educational Qualifications of customers (which is stored in one location) and there is another dataset on Customer ID, Units sold etc. and SAS can also merge or append such data sets by the common variable, Customer ID.