Final Exam: Big Data Infrastructures
Big Data 2021 | Beginner
- 1 Video | 32s
- Includes Assessment
- Earns a Badge
Final Exam: Big Data Infrastructures will test your knowledge and application of the topics presented throughout the Big Data Infrastructures track of the Skillsoft Aspire Data for Leaders and Decision Makers Journey.
WHAT YOU WILL LEARN
recognize the need for Big Dataname and describe the role of the main layers of Big data analytics from the bottom to the topdefine the role of the data processing layer and specify how information captured in the previous layer is processeddescribe Spark and how it offers open-source scalable massively parallel in-memory solutions for analytics applicationslist the main characteristics of Spark such as loading behavior, file formats, parallelism, cache, data skewsname most important performance optimization techniques such as file format selection, level of parallelism and API selectiondescribe the concept of Big Data and the history behind itidentify the sources that are capable of generating Big Datadefine the big 7 characteristics that define Big Datadescribe the subcomponents of Hadoop such as MapReduce and HDFS
describe the difference between horizontal and vertical scalingname and describe the features of Storage systems such as HDFS, S3 and Object stores, Elastic Search and Apache Solr, Kudu, CockroachDBdescribe the rewarding role of NoSQL databases in horizontal distribution of large, structured and unstructured dataspecify when to use NoSQL and when to use SQL databasespecify use cases, benefits and challenges of popular key-value data storesdescribe graph database use cases and specify why the relationship between data is as important as the data itself in a graph databasespecify the shortcoming of distributed systems and why these shortcomings make Big Data even more importantdescribe what horizontal scaling is and specify how it eliminates the need for adding more memory to existing machines by using clusters (AKA, Sharding )name and describe the four types of Big Data Analytics (i.e. Prescriptive, Predictive, Diagnostic, Descriptive)describe the challenges in the current data analytics models and system designs such as scalability, consistency, reliability, efficiency, and maintainability
IN THIS COURSE
1.Big Data Infrastructures33sUP NEXT
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