![]() Learn more in this Ask the Expert session. SAS Studio includes comprehensive integration with Git, a system for tracking changes and managing version control among multiple users. The days of scheduling and needing to leave your PC on are gone! You can now set up a program or code from a task to schedule and it will run as needed. You can find a guide to getting started here. You can easily build your own custom tasks (software developer skills not required) so others without SAS coding skills can utilise them. SAS Studio comes with many enhancements and cool new functionality: It is all centrally managed, secure, auditable and governed. It is distributed, fault tolerant, elastic and can work on problems larger than the available RAM. SAS Viya has CAS, the next generation SAS run time environment which makes use of both memory and disk. ![]() Previously SAS 9 had the compute server aka the workspace server as the processing engine. SAS Studio (v5.2 onwards) works on SAS Viya. So what cool things can you do with SAS Studio? 2. You can build queries to join data, create simple and complex expressions, filter and sort data.īut it does much more than that. You can code or use the tasks to perform analysis. It allows you to access your data, libraries and existing programs and import a range of data sources including Excel and CSV. And SAS Studio is brought to you by the same SAS R&D developers who maintain SAS Enterprise Guide. Since there is nothing to install on your desktop, you can access it from almost any machine: Windows or Mac. It is the browser-based interface for SAS programmers to run code or use predefined tasks to automatically generate SAS code. fraud detection (to detect misuse of vouchers).įirstly, let's answer the "what is SAS Studio" question.marketing analytics (to look at customer behaviour and build successful campaigns).supply chain (to look at wastage and stock availability). ![]() EG is used widely across several supermarket operations, including: SAS STUDIO | A COMPARISONįor the last nine months I have been working with one of the UK’s largest supermarket answering that exact question as they make that journey from SAS Enterprise Guide to SAS Studio. So why move to SAS Studio? Why should I leave the comfort of what works? SAS ENTERPRISE GUIDE vs. SAS Enterprise Guide, or EG as it is commonly known as, is a mature SAS product with many years of R&D, an established user base, a reliable and trusted product. Whether you’re looking to access SAS data or import good old Excel locally, join data together or perform data analysis, a few clicks and ta-dah, you’re there! Alternatively, if you insist on coding or like me, use a bit of both, the ta-dah point still holds. It is easy to use, the interface intuitive, a Swiss Army knife when it comes to data analysis. It has been not just my go-to tool, but that of many of the SAS customers I have worked with over the years. Reprex package is meant for.As a SAS consultant I have been an avid user of SAS Enterprise Guide for as long as I can remember. ![]() If you’re asking for R help, reporting a bug, or requesting a new feature, you’re more likely to succeed if you include a good reproducible example, which is precisely what the Getting Started guide or, for more detailed examples, go straight to the These packages provide a comprehensive foundation for creating and using models of all types. Tidymodels packages, which largely replace the Modeling with the tidyverse uses the collection of Paste() that makes it easier to combine data and strings. Piping operators (like %$% and %%) that can be useful in other places. It also provide a number of more specialised Purrr, which provides very consistent and natural methods for iterating on R objects, there are two additional tidyverse packages that help with general programming challenges: dbplyr allows you to use remote database tables by converting dplyr code into SQL.ĭata.table backend by automatically translating to the equivalent, but usually much faster, data.table code. ![]() There are also two packages that allow you to interface with different backends using the same dplyr syntax: You’ll need to pair DBI with a database specific backends likeĭplyr, there are five packages (includingįorcats) which are designed to work with specific types of data: Readr, for reading flat files, the tidyverse package installs a number of other packages for reading data: They are not loaded automatically with library(tidyverse), so you’ll need to load each one with its own call to library(). The tidyverse also includes many other packages with more specialised usage. R uses factors to handle categorical variables, variables that have a fixed and known set of possible values. Forcats provides a suite of useful tools that solve common problems with factors. ![]()
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