How to use Suggestions in SAS® Data Studio
SAS Technical Training Consultant Mary Kathryn Queen introduces you to SAS Data Studio's Suggestions feature.
Author
Mary Kathryn QueenRSS
Principal Technical Training Consultant
Principal Technical Training Consultant
Mary Kathryn Queen is a Principal Technical Training Consultant in the Global Enablement and Learning (GEL) Team within SAS R&D's Global Technical Enablement Division. Her primary focus is on SAS Data Management technologies, particularly data quality, data preparation, and data governance.
SAS Data Studio Code Transform (Part 2)
This is a continuation of my previous blog post on SAS Data Studio and the Code transform. In this post, I will review some additional examples of using the Code transform in a SAS Data Studio data plan to help you prepare your data for analytic reports and/or models. Create
SAS Data Studio Code Transform (Part 1)
SAS Data Studio is a new application in SAS Viya 3.3 that provides a mechanism for performing simple, self-service data preparation tasks to prepare data for use in SAS Visual Analytics or other applications. It is accessed via the Prepare Data menu item or tile on SAS Home. Note: A
SAS Data Preparation 2.1: Data quality transformations
SAS Data Preparation 2.1 is now available and it includes the ability to perform data quality transformations on your data using the definitions from the SAS Quality Knowledge Base (QKB). The SAS Quality Knowledge Base is a collection of files which store data and logic that define data quality operations
Load Data into SAS Viya via REST API
In this blog post I am going to cover the example of importing data into SAS Viya using Cloud Analytic Services (CAS) actions via REST API. For example, you may want to import data into a CASLib via REST API. This means you can perform an import of data outside
SAS Viya 3.2: Visual Data Builder
In SAS Viya 3.2, SAS Visual Data Builder provides a mechanism for performing simple, self-service data preparation tasks for SAS Visual Analytics or other applications. SAS Visual Data Builder is NOT an Extract, Transform and Load (ETL) or data quality tool. You may still need one of those tools to
The Self-Service Import in SAS Viya 3.2
In SAS Viya 3.2, the Self-Service Import provides a mechanism for a user to import (copy) data into the SAS Cloud Analytic Services (CAS) environment. The data is copied as a .sashdat file into the selected CAS Library location when it is imported. Self-Service Import data can only be imported into
Securing sensitive data using SAS Federation Server data masking
SAS® Federation Server provides a central, virtual environment for administering and securing access to your data. It also allows you to combine data from multiple sources without moving or copying the data. SAS Federation Server Manager, a web-based application, is used to administer SAS Federation Server(s). Data privacy is a
Securing sensitive data using SAS Federation Server at the row and column level
SAS® Federation Server provides a central, virtual environment for administering and securing access to your data. It also allows you to combine data from multiple sources without moving or copying the data. SAS Federation Server Manager, a web-based application, is used to administer SAS Federation Server(s). Data privacy is a
Securing sensitive data using SAS Federation Server at the data source level
Data virtualization is an agile way to provide virtual views of data from multiple sources without moving the data. Think of data virtualization as an another arrow in your quiver in terms of how you approach combining data from different sources to augment your existing Extract, Transform and Load ETL batch
Using multiple SAS Quality Knowledge Base locales in a SAS Event Stream Processing compute window
In a previous blog post, I demonstrated combining the power of SAS Event Stream Processing (ESP) and the SAS Quality Knowledge Base (QKB), a key component of our SAS Data Quality offerings. In this post, I will expand on the topic and show how you can work with data from
Using SAS Quality Knowledge Base Definitions in a SAS Event Stream Processing Compute Window
The SAS Quality Knowledge Base (QKB) is a collection of files which store data and logic that define data cleansing operations such as parsing, standardization, and generating match codes to facilitate fuzzy matching. Various SAS software products reference the QKB when performing data quality operations on your data. One of
Using an alternate Quality Knowledge Base (QKB) in a DataFlux Data Management Studio data job
In DataFlux Data Management Studio, the predominate component of the SAS Data Quality bundle, the data quality nodes in a data job use definitions from something called the SAS Quality Knowledge Base (QKB). The QKB supports over 25 languages and provides a set of pre-built rules, definitions and reference data
Using Multiple Quality Knowledge Base Locales in a DataFlux Data Management Studio Data Job
In DataFlux Data Management Studio, the data quality nodes (e.g., Parsing, Standardization, and Match Codes) in a data job use definitions from the SAS Quality Knowledge Base (QKB). These definitions are based on a locale (Language and Country combination). Sometimes you would like to work with multi-locale data within the
Improving matching results in DataFlux Data Management Studio with cluster comparison
Trusted data is key to driving accurate reporting and analysis, and ultimately, making the right decision. SAS Data Quality and SAS Data Management are two offerings that help create a trusted, blended view of your data. Both contain DataFlux Data Management Studio, a key component in profiling, enriching monitoring, governing
DataFlux Data Management Server 2.7: REST APIs
REpresentational State Transfer (REST) is an architectural style for designing web services that access a system's resources using HTTP methods. With the release of DataFlux Data Management 2.7 earlier this year, three new REST Application Programming Interfaces (APIs) are now available: Data Management Server Batch Jobs Data Management Server Real-time
Matching Names: How to Avoid a Common Mistake
Sometimes when trying to fuzzy match names you want to fuzzy match just a portion of the name: for example, Family Name and/or Given Name. A common mistake that people make is to feed in the Family Name and Given Name columns separately into the Match Codes node instead of