M 2 Data Analytics Lifecycle
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Transcript of M 2 Data Analytics Lifecycle
Data Analytics LifecycleB.Bhuvaneswaran
Assistant Professor (SS)Department of Computer Science & Engineering
Rajalakshmi Engineering CollegeThandalam
Chennai – 602 [email protected]
Phase 1: Discovery Phase 2: Data Preparation Phase 3: Model Planning Phase 4: Model Building Phase 5: Communicate Results Phase 6: Operationalize
Phase 1: Discovery Learn the business domain, including relevant history,
such as whether the organization or business unit has attempted similar projects in the past, from which you can learn.
Assess the resources you will have to support the project, in terms of people, technology, time, and data.
Frame the business problem as an analytic challenge that can be addressed in subsequent phases.
Formulate initial hypotheses (IH) to test and begin learning the data.
Question? (Ref. Module-2, Page-16) In which lifecycle stage are initial
hypotheses formed? A. Discovery B. Model planning C. Model building D. Data preparation
Of all of the phases, the step of Data Preparation is generally the most iterative and time intensive.
Question? (Ref. Module-2, Page-20) In which phase of the data analytics
lifecycle do Data Scientists spend the most time in a project? A. Discovery B. Data Preparation C. Model Building D. Communicate Results
Phase 4: Model Building Develop data sets for testing, training, and
production purposes. Get the best environment you can for
executing models and workflows, including fast hardware and parallel processing.
Question? (Ref. Module-2, Page-29) In which lifecycle stage are test and
training data sets created? A. Model building B. Model planning C. Discovery D. Data preparation
Question? (Ref. Module-2, Page-29) In which lifecycle stage are appropriate
analytical techniques determined? A. Model planning B. Model building C. Data preparation D. Discovery
Question? (Ref. Module-2, Page-31) In which phase of the analytic lifecycle
would you expect to spend most of the project time? A. Discovery B. Data preparation C. Communicate Results D. Operationalize
Question? (Ref. Module-2, Page-33) Which activity is performed in the
Operationalize phase of the Data Analytics Lifecycle? A. Define the process to maintain the model B. Try different analytical techniques C. Try different variables D. Transform existing variables
Question? (Ref. Module-2, Page-37) What is an appropriate data visualization
to use in a presentation for an analyst audience? A. Pie chart B. Area chart C. Stacked bar chart D. ROC curve
References Data Science and Big Data Analytics
(DSBDA), EMC.