dat476 | undergraduate
Query Construction For Large Scale Data
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Security, Governance, and Risk Control
- Create a data security and governance plan for an organizationâs Big Data implementation.
- Explain organizational prerequisites leaders should consider when addressing Big Data procurement, security considerations, real-time support issues, performance considerations, and use of Cloud Technology.
- Explain Hadoop features and why they are useful to Data Scientists.
- Identify the strengths and resolve the vulnerabilities of an organizationâs Big Data security and governance plans and policies.
Big Data Processes
- Critique an organizationâs big data processes, identify improvement opportunities, and recommend solutions for each identified opportunity.
- Identify strategic opportunities of Big Data that could benefit the organization.
- Discuss Big Data business cases to identify strengths and opportunities in maximizing effectiveness of Big Data processes.
- Evaluate an organizationâs current Big Data processes and assess their ability to support data science in the organization.
Query Troubleshooting Methods and Tools
- Develop a troubleshooting methodology supported by resources, methods, and tools, for resolving Big Data query issues.
- Examine broken Big Data queries and use troubleshooting methods to resolve each queryâs bugs and issues.
- Document the troubleshooting methodology used and apply it to solve broken queries.
Big Data Queries and Data Sources
- Create Big Data queries appropriate to an organizationâs big data sources and structures that obtain information to enable decision-making.
- Construct query design recommendations within an organizationâs current Big Data architecture and other constraints that improve query performance and query construction.
- Build a query following a given design that obtains the information requested to resolve an organizationâs issue.
- Recommend Big Data technology, sources and structures, to support an organizationâs goal and strategies.
Big Data Technology Components
- Examine Big Data technology components, algorithms, and methods, and apply them to data environments and organizational problems.
- Apply data modeling using Hadoop.
- Apply the steps in the Big Data Analytics Lifecycle to a Big Data project.
- Apply Big Data algorithms to solve data analysis problems and enable effective and efficient data retrieval.
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