Become a SAS® Certified Big Data Professional.
Demonstrate your ability to use the tools and technology designed to handle big data. The SAS Certified Big Data Professional program delivers the extra edge you're looking for.
Course content is designed to prepare you for the certification exams.
Real-world case studies enable you to apply what you have learned.
Pass both exams to earn your certification credential.
To enroll in the program, you need at least six months of programming experience in SAS or another programming language. If you need to brush up on your programming skills, the SAS Programming for Data Science Fast Track will give you a good foundation.
This course provides an overview of the challenges associated with big data and analysis-driven data.
In this course, you'll learn how to use SAS Visual Analytics Explorer to explore in-memory tables from the SAS® LASR™ Analytic Server and perform advanced data analyses.
This introductory SAS/STAT® course focuses on t-tests, ANOVA and linear regression, and includes a brief introduction to logistic regression.
In this course, you'll learn how to perform data management tasks, such as improving data quality, entity resolution and data monitoring.
Storytelling is a necessary skill when talking to key stakeholders. Insights uncovered in your data can move mountains if the right people say yes. But how do you move someone from simply being curious, all the way to, "Let's do this!" In this course, you'll learn why storytelling is a skill you need to develop, when a story works and when it doesn't, and how to communicate data in a meaningful way.
This course teaches you how to use SAS programming methods to read, write and manipulate Hadoop data. You'll learn how to use Base SAS methods to read and write raw data with the DATA step, manage the Hadoop Distributed File System (HDFS) and execute MapReduce and Pig code from SAS via the HADOOP procedure. You'll also learn how to use SAS/ACCESS® Interface to Hadoop methods that allow LIBNAME access and SQL pass-through techniques to read and write Hive or Impala table structures.
This course focuses on DS2, a fourth-generation SAS proprietary language for advanced data manipulation, which enables parallel processing and storage of large data with reusable methods and packages.
In this course, you will use processing methods to prepare structured and unstructured big data for analysis. You will learn to organize the data into structured tabular form using Apache Hive and Apache Pig. You will also learn SAS software technology and techniques that integrate with Hive and Pig, as well as how to use these open source capabilities by programming with Base SAS and SAS/ACCESS Interface to Hadoop, and with SAS Data Integration Studio.
This course focuses on accessing data on the SAS LASR Analytic Server and performing exploratory analysis and preparation. Topics include starting the server, loading data and manipulating data on the SAS LASR Analytic Server using the IMSTAT procedure. IMSTAT topics include deriving new temporary and permanent tables and columns, calculating summary statistics (e.g., mean, frequency and percentile), and creating filters and joins on in-memory data.
Learn to manage big data, focusing on data quality and visual data exploration for advanced analytics, plus communication skills.Select
Learn analytical modeling, machine learning, experimentation, forecasting and optimization.Select
Learn it all. This program includes all coursework from both the big data and advanced analytics programs.Select
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