When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
Working with SAS(R) Data Loader for Hadoop
This course gives business analysts and data scientists a seamless platform to profile, integrate, cleanse, and move big data without writing code in a Hadoop environment using an intuitive web-based...
Read MoreThis course gives business analysts and data scientists a seamless platform to profile, integrate, cleanse, and move big data without writing code in a Hadoop environment using an intuitive web-based interface.
Skills Gained
- move data in and out of Hadoop
- interrogate and profile data for quality issues
- transform, transpose, and join data that is fit-for-purpose
- cleanse and integrate data suitable for analysis and reporting
- perform master data management activities of record clustering and survivorship in Hadoop
- load data into the SAS In-Memory Analytics Server for analytics and exploration
- execute custom SAS and HiveQL code inside the Hadoop cluster
- chain custom-built data management flows into re-useable jobs.
Who Can Benefit
- Business users who interact with data, perform data discovery, query data, and ensure that data is in the proper place and format for other users; data analysts, data scientists, and statisticians who review results of data discovery activities, create new tables, create new data elements, change the format/structure of data tables to view them in a variety of ways, manipulate and score data elements, and load data for use by other users; and data management specialists who apply enterprise standards to the data, ensure data quality throughout the enterprise, move data into and out of the Hadoop cluster, and optimize code running in the Hadoop cluster
Prerequisites
- There are currently no prerequisites for this course.
Course Details
Introduction to Big Data and Hadoop
- big data and Hadoop
- Hadoop ecosystem
SAS Data Loader Overview
- SAS Data Loader capabilities and architecture
- SAS Data Loader directives and tasks
- steps common to most directives
- preparing data for analysis and reporting
- course overview and logistics
Acquiring and Discovering Data
- introduction to acquiring and discovering data
- copying a table into Hadoop
- importing a delimited file into Hadoop
- profiling data for inconsistencies
- querying data for relevant columns and rows
Transforming and Transposing Data
- introduction to transforming and transposing data
- transforming data to be fit-for-purpose
- transposing data for use in analysis and reporting
Cleansing Data
- introduction to cleansing data
- parsing data into meaningful subsets
- standardizing data into consistent formats
- using match codes to determine data similarity
- using names to identify gender
- analyzing data for data types
- applying casing for data consistency
- extracting data in useful tokens
- analyzing data for inconsistent patterns
Integrating Data
- introduction to integrating data
- joining data in Hadoop
- sorting and de-duplicating data
- clustering and surviving data to determine a best record
- matching and merging data into a single table
- deleting rows in Hadoop tables
- running user-written programs inside Hadoop
Delivering Data
- introduction to delivering data from Hadoop
- loading data to the SAS LASR Analytic Server for analysis and reporting
- copying Hadoop data to SAS and relational database tables
Managing and Integrating Directives
- introduction to managing and integrating directives
- creating data flows by chaining directives
- integrating directives into SAS platform applications
- running directives as batch jobs
Additional Topics
- SAS and Hadoop data processing
- SAS DS2 programs
- debugging Hadoop jobs
