Dell Exam: Data Science and Big Data Analytics certification

Big Data, Analytics, and the Data Scientist Role(5%)

– Define and describe the characteristics of Big Data- Describe the business drivers for Big Data analytics and data science

– Describe the Data Scientist role and related skills

Data Analytics Lifecycle(8%)

– Describe the data analytics lifecycle purpose and sequence of phases- Discovery -Describe details of this phase, including activities and associated roles

– Data preparation -Describe details of this phase, including activities and associated roles

– Model planning -Describe details of this phase, including activities and associated roles

– Model building -Describe details of this phase, including activities and associated roles

Initial Analysisof the Data(15%)

– Explain how basic R commands are used to initially explore and analyze the data- Describe and provide examples of the most important statistical measures and effective visualizations of data

– Describe the theory, process, and analysis of results for hypothesis testing and its use in evaluating a model

Advanced Analytics -Theory, Application, and Interpretation of Results for Eight Methods(40%)

Describe theory, application, and interpretation of results for the following methods:

• K-means clustering
• Association rules
• Linear regression
• Logistic Regression
• Naïve Bayesian classifiers
• Decision trees
• Time Series Analysis
• Text Analytics

Advanced Analytics for Big Data -Technology and Tools(22%)

– Describe the technological challenges posed by Big Data- Describe the nature and use of MapReduce and Apache Hadoop

– Describe the Hadoop ecosystem and related product use cases

– Describe in-database analytics and SQL essentials

– Describe advanced SQL methods: window functions, ordered aggregates, and MADlib

Operationalizing an Analytics Project and Data Visualization Techniques(10%)

– Describe best practices for communicating findings and operationalizing an analytics project- Describe best practices for building project presentations for specific audiences

– Describe best practices for planning and creating effective data visualizations