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Released: 11/2018 Duration: 57m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 134 MB Level: Intermediate | Genre: eLearning | Language: English Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to conduct exploratory data analytics with GCP. First, review the concepts of segmentation and profiling. Then get hands on, as you learn to perform both text and visual analysis of data using tools provided by GCP: Cloud Datalab, BigQuery, Cloud Dataflow, and Data Studio. Finally, look at an end-to-end use case that applies what you've learned in the course.  Released: 09/2018 Duration: 1h | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 134 MB Level: Intermediate | Genre: eLearning | Language: English Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by veteran cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to design and build data warehouses using GCP. Explore the different types of storage options available in GCP for files, relational data, documents, and big data, including Cloud SQL, Cloud Bigtable, and Cloud BigQuery. Then learn how to use one solution, BigQuery, to perform data storage and query operations, and review advanced use cases, such as working with partition tables and external data sources. Finally, learn best practices for table design, storage and query optimization, and monitoring of data warehouses in BigQuery.  Released: 09/2019 Duration: 2h 7m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 309 MB Level: Beginner | Genre: eLearning | Language: English The hype about big data may have peaked several years ago, but big data is far from gone. Instead it forms the foundation for some of today's most exciting technologies. Artificial intelligence (AI), machine learning, and data science rely on big data, or data that—by virtue of its velocity, volume, or variety—can't be easily stored or analyzed with traditional methods. In this nontechnical course, Barton Poulson digs into the topic of big data, explaining how it works and shapes our modern data universe. Barton explains big data's relationship to AI, data science, social media, and the Internet of Things (IoT). He goes over some of the ethical issues behind the use of big data. Plus, he covers techniques involved in analyzing big data, including data mining and predictive analytics.  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