Docsity
Docsity
Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity

Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan

Guidelines and tips
Guidelines and tips
Sell on Docsity
Sell on Docsity
Docsity AI
Docsity AI
Log inSign up

Prepare for your exams

Study with the several resources on Docsity

Find documents

Prepare for your exams with the study notes shared by other students like you on Docsity

Search for your university

Find the specific documents for your university's exams

Docsity AINEW

Summarize your documents, ask them questions, convert them into quizzes and concept maps

Explore questions

Clear up your doubts by reading the answers to questions asked by your fellow students

Earn points to download

Earn points by helping other students or get them with a premium plan

Share documents
download point icon20 Points

For each uploaded document

Answer questions
download point icon5 Points

For each given answer (max 1 per day)

All the ways to get free points
Get points immediately

Choose a premium plan with all the points you need

Study Opportunities

Choose your next study program

Get in touch with the best universities in the world. Search through thousands of universities and official partners

Community

Ask the community

Ask the community for help and clear up your study doubts

Free resources

Our save-the-student-ebooks!

Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors

Data Science Lifecycle Phases and Objectives, Exams of Data Mining

Alexandria UniversityData Mining

An overview of the key phases and objectives in the data science lifecycle, including data discovery, model planning, model building, communicating results, and operationalizing the model. It covers important concepts such as initial hypotheses, model deployment, and the roles of various stakeholders like business users, data scientists, and project managers. The document delves into the specific goals and activities within each phase of the data analytics lifecycle, helping readers understand the end-to-end process of transforming data into actionable insights and business value. With a focus on best practices and common challenges, this resource can be valuable for students, professionals, and anyone interested in the practical application of data science methodologies.

Typology: Exams

2021/2022

Uploaded on 11/25/2022

shehab-eldin-said
shehab-eldin-said 🇪🇬

6 documents

1 / 5

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
Data Science
Sheet #3
1. …. Is the 5th phase in Data Analytics Lifecycle
a. Communicate Results
b. Model Building
c. Model Planning
d. Operationalize
2. In Communicate Results phase we need to
a. Compare outcomes of the modeling to the criteria established
b. Compare the results to Initial Hypotheses (IH)
c. Know the results effects on Business
d. All of them
3. Operationalize Phase objectives include
a. Access the model benefits
b. Implement the model in productive environment on a small scale
c. Implement ongoing monitoring of model accuracy
d. All of them
4. Technical documents and Final reports are delivered in
a. Operationalize Phase
b. Model Building Phase
c. Model Planning Phase
d. Communicate Results Phase
5. After Communicate Results Phase we can decide to rebuild the model
a. True
b. False
6. Initial Hypotheses are formulated in …. And compared to results obtained from …
a. Discovery Phase, Communicate Results Phase
b. Discovery Phase, Model Planning Phase
c. Model Building Phase, Communicate Results Phase
d. Discover Phase, Operationalize Phase
7. Deploying on a wide scale basis is not recommended at first to minimize risk
a. True
b. False
8. In Operationalize Phase, processes to update, retain and retire the model are defined
a. True
b. False
9. In Communicate Results Phase we quantify business value
a. True
Page 1
pf3
pf4
pf5

Partial preview of the text

Download Data Science Lifecycle Phases and Objectives and more Exams Data Mining in PDF only on Docsity!

Data Science

Sheet

  1. …. Is the 5 th^ phase in Data Analytics Lifecycle a. Communicate Results b. Model Building c. Model Planning d. Operationalize
  2. In Communicate Results phase we need to a. Compare outcomes of the modeling to the criteria established b. Compare the results to Initial Hypotheses (IH) c. Know the results effects on Business d. All of them
  3. Operationalize Phase objectives include a. Access the model benefits b. Implement the model in productive environment on a small scale c. Implement ongoing monitoring of model accuracy d. All of them
  4. Technical documents and Final reports are delivered in a. Operationalize Phase b. Model Building Phase c. Model Planning Phase d. Communicate Results Phase
  5. After Communicate Results Phase we can decide to rebuild the model a. True b. False
  6. Initial Hypotheses are formulated in …. And compared to results obtained from … a. Discovery Phase, Communicate Results Phase b. Discovery Phase, Model Planning Phase c. Model Building Phase, Communicate Results Phase d. Discover Phase, Operationalize Phase
  7. Deploying on a wide scale basis is not recommended at first to minimize risk a. True b. False
  8. In Operationalize Phase, processes to update, retain and retire the model are defined a. True b. False
  9. In Communicate Results Phase we quantify business value a. True

b. False

  1. To ensure that the new model fits smoothly into the production environment we do a small scope deployment a. True b. False
  2. ……… describes how a data analytics project is executed a. Data analytics graph b. Data analytics flow c. Data analytics lifecycle d. Flowcharts
  3. In data analytics lifecycle, it is necessary to move in only one direction between phases a. True b. False
  4. ……….. are found in the first phase of data analytics lifecycle, form the basis of the tests you will analyze in later phases. a. Data b. Resources c. Interviews d. Hypotheses
  5. ………. represents the last step of preparations before executing the analytical model. a. Model planning b. Model preparation c. Model building d. All of the above
  6. Model Planning is a preparation step in in data science life cycle. a. True b. False
  7. The model is defined in which phase. a. Data discovery b. Model preparation c. Model building d. Model planning
  8. goals of model planning and model building are a. different b. the same c. shared d. overlapped

c. Data engineer d. Database Administrator

  1. ___________ a person or group who provides resources and support for the project, program or portfolio and is accountable for enabling success. a. Project manager b. Business intelligence analyst c. Business user d. Project sponsor
  2. True or false? The phases of data analytics are data discovery, data model execution, communication of the results, and operationalization only. a. True b. False
  3. True or false? The business user can be involved from the stage of defining the value of the data initiative. a. True b. False
  4. ___________ ensures there is quality in the deliverables of the final data product and ensures to deliver the project on-time and on-budget leveraging all the resources on the project. a. Business user b. project sponsor c. project manager d. Data scientist
  5. During the phase of ___________, the stakeholders constantly analyze the business trends, similar data analytics case studies, and domain of the business industry. a. Operationalization b. Model planning c. Data discovery d. Data preparation
  6. True or false? ETL stands for Extract, Transform and Load, which is a process used to collect data from various sources, transform the data depending on business rules/needs and load the data into a destination database. a. True b. False
  7. In the model planning phase, to determine the suitable method must be based on_________. a. hypotheses b. data structure c. data volume d. All of the above
  8. Do I have a good idea about the type of model to try?” __________ question.

a. Data preparation b. Data discovery c. Model building d. None of the above

  1. The main resource in discovery phase is/are__________. a. Data validity b. Working team c. Project time d. All of the above True or false? Business User benefits from the end results and can consult and advise project team on value of end results and how these will be operationalized. e. True f. False