In this 1.25-hour long project-based course, you will learn to explain the highlights of the history of SAS, how to access and explore SAS Studio and how to transfer a NOTEPAD file into SAS Studio. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

By the end of this project, you will have written SQL queries to retrieve data from a database table in LibreOffice Base. While Base includes a WYSIWYG query utility, learning to access data using SQL provides an additional measure of control over the data retrieval process. In addition, SQL skills can be applied across a variety of relational database management systems in addition to LibreOffice Base. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

This is a self-paced lab that takes place in the Google Cloud console. In this lab you explore various ways to load data into Cloud Spanner as well as perform a backup of your database.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will learn how to migrate an application running on Apache Cassandra™ to DataStax Enterprise (DSE). To do this, you will deploy a Cassandra™ database and an application that writes data into it. You will then deploy a DataStax Enterprise database and connect the same application to the database. Finally, you will learn how to migrate data from Apache Cassandra™ to DSE using the The DataStax Bulk Loader dsbulk.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use the What-if Tool to identify potential biases in a model trained on mortgage loan applications.

This is a self-paced lab that takes place in the Google Cloud console. In this lab you’ll be working with Wrangler directives which are used by the Wrangler plugin, the “Swiss Army Knife” of plugins in the Data Fusion platform, so that your transformations are encapsulated in one place and we can group transformation tasks into manageable blocks.

This course is the eighth course in the Google Data Analytics Certificate. You’ll have the opportunity to complete an optional case study, which will help prepare you for the data analytics job hunt. Case studies are commonly used by employers to assess analytical skills. For your case study, you’ll choose an analytics-based scenario. You’ll then ask questions, prepare, process, analyze, visualize and act on the data from the scenario. You’ll also learn other useful job hunt skills through videos with common interview questions and responses, helpful materials to build a portfolio online, and more. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Learn the benefits and uses of case studies and portfolios in the job search. - Explore real world job interview scenarios and common interview questions. - Discover how case studies can be a part of the job interview process. - Examine and consider different case study scenarios. - Have the chance to complete your own case study for your portfolio.

The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

This is the second course in Java Database Connectivity (JDBC) and builds upon the core principals and techniques in the JDBC 1 course. It utilizes PreparedStatements, highlighting their advantages over JDBC Statements. It will also introduce utilizing Stored Procedures on the database server itself to encapsulate complex SQL and PLSQL logic. The Course also introduces the idea of querying the database meta data such as table structures and how to cope with different SQL syntax for different Jdbc complaint databases via the JDBC escape syntax.

This course is aimed at students wishing to learn how Java interacts with databases in a modern framework. The course uses the very popular Spring Boot Framework, with Micro services, as a setting for our database interactions using Java Persistence Framework (JPA) and Spring Data Repositories to abstract away JPA. Students will then learn how to expose Repositories as Rest Web services in their own right using Hypermedia as the Engine of Application State or HATEAOS concepts. Spring Aspect Oriented Programming (AOP) will be covered to illustrate how cross cutting concerns like logging can be applied in a centralized non evasive manner to domain classes. finally the course covers the use of Spring Transaction Managers and Springs declarative configuration Transaction model.