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Effective Communication in the Globalised Workplace - The Capstone
by Lee Kooi Cheng , Wu Siew Mei- 4.6
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Approx. 5 hours to complete
Capstone: Data Collection 1 Data Collection Part 1 Data Collection Part 2 Data Collection Part 3 Data Collection Part 4 Capstone: Data Collection 2 Data Collection - Email Request Part 1 Data Collection - Email Request Part 2...
Big data and Language 2
by Seonmin Park- 0.0
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Approx. 5 hours to complete
Considerations of Big Data and Language Big Data for Different Languages Limitations of Big Data Future directions of Big Data...
Getting Started on Mainframe with z/OS Commands and Panels
by Jeff Bisti- 4.7
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Approx. 15 hours to complete
Lab Allocate new data sets Working with Data Sets Allocating a data set in TSO Working with data sets Allocating a data set in TSO Working with data sets Lab Copy, Move, Rename, Delete Data Sets and Members Lab data set lists Use ISPF/PDF to allocate data sets and edit data sets using the ISPF Editor primary and line commands...
Getting Started with SAS Visual Analytics
by Nicole Ball- 4.7
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Approx. 5 hours to complete
In this course, you learn more about SAS Visual Analytics and the SAS Viya platform, how to access and investigate data in SAS Visual Analytics, and how to prepare data for analysis using SAS Data Studio. Preparing Data Using SAS Data Studio Introduction to Preparing Data Data Types Demo: Accessing and Investigating Data...
Big Data Analytical Platform on Alibaba Cloud
by Derek Meng- 4.5
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Approx. 8 hours to complete
This course is designed to teach engineers how to use Alibaba Cloud Big Data products. Alibaba Cloud Big Data - Data Integration: https://edu. Big Data on Alibaba's Double 11 Introduction to Hadoop in Big Data Ecosystem Big Data Product Overview Eight Things You Should Know about Big Data Big Data Application: Technical Architecture of a Big Data Platform...
Getting Started with SAS Programming
by Stacey Syphus- 4.8
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Approx. 22 hours to complete
It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. Using the DATA Step to Create a SAS Data Set DATA Step Processing Demo: Working with the DATA Step Preparing Data Analyzing and Reporting on Data Examples of Procedures that Analyze Data Analyzing and Reporting on Data...
Building a Data Science Team
by Jeff Leek, PhD , Brian Caffo, PhD , Roger D. Peng, PhD- 4.5
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Approx. 6 hours to complete
Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. How the data science team relates to other teams in an organization What are the expected qualifications of different data science team members Relevant questions for interviewing data scientists...
Creating New BigQuery Datasets and Visualizing Insights
by Google Cloud Training- 4.6
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Approx. 11 hours to complete
This is the second course in the Data to Insights specialization. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Google Data Studio. Storing and Exporting Data Demo: Importing JSON Data Ingesting New Data into BigQuery Demo: Loading Data into BigQuery Data Visualization Overview of Data Visualization principles...
Preparing for the Google Cloud Professional Data Engineer Exam
by Google Cloud Training- 4.6
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Approx. 9 hours to complete
Understanding the Professional Data Engineer Certification Understanding the Professional Data Engineer certification Designing Data Processing Systems Designing flexible data representations Design data pipelines Design data processing infrastructure Designing Data Processing Systems: Exam Guide Review Building and Operationalizing Data Processing Systems Building data processing systems Building and Operationalizing Data Processing Systems: Exam Guide Review...
Data Warehouse Concepts, Design, and Data Integration
by Michael Mannino- 4.4
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Approx. 22 hours to complete
This is the second course in the Data Warehousing for Business Intelligence specialization. * Evaluate an organization for data warehouse maturity and business architecture alignment; * Create a data warehouse design and reflect on alternative design methodologies and design goals; * Create data integration workflows using prominent open source software; Data Warehouse Concepts and Architectures...
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