Match each component of the Data Analytic Life Cycle from the column on the left to definitions from the column on the right: •V A. Communicate Results 1-Change business environment and evolving needs for decision support and analytics by implementing ad hoc decisions that arise episodically. - v B. Discovery 2- Compare model outcomes to establish criteria for falure and success. Data Preparation 3. Prepare to deploy new approach or models in a production environment and communicate insights to diverse Operationalize stakeholders. Model Planning 4. Develop datasets for training, testing and production. - v Model Building S- Data science team identifies models for clustering and conduct data exploration and variable selection. 6. Prepare data analytic sandbox and perform extraction, loading and transformations. 7. Data science team investigates the problem and develop context to determine which resources to collect.

Match each component of the Data Analytic Life Cycle from the column on the left to definitions from the column on the right: •V A. Communicate Results 1-Change business environment and evolving needs for decision support and analytics by implementing ad hoc decisions that arise episodically. - v B. Discovery 2- Compare model outcomes to establish criteria for falure and success. Data Preparation 3. Prepare to deploy new approach or models in a production environment and communicate insights to diverse Operationalize stakeholders. Model Planning 4. Develop datasets for training, testing and production. - v Model Building S- Data science team identifies models for clustering and conduct data exploration and variable selection. 6. Prepare data analytic sandbox and perform extraction, loading and transformations. 7. Data science team investigates the problem and develop context to determine which resources to collect.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Concept explainers

Single Table

In a database management system, a single table is designed to obtain data of heterogeneous items. A single-table design with DynamoDB resolves the issue of raising multiple requests for the relevant data of an entity.

Question

I need to match both columns

Match each component of the Data Analytic Life Cycle from the column on the left to definitions from the column on the right:
1. Change business environment and evolving needs for decision support and analytics by implementing ad hoc
decisions that arise episodically.
A. Communicate Results
B. Discovery
2. Compare model outcomes to establish criteria for failure and success.
Data Preparation
3. Prepare to deploy new approach or models in a production environment and communicate insights to diverse
Operationalize
stakeholders.
Model Planning
4.
Develop datasets for training, testing and production.
Model Building
5. Data science team identifies models for clustering and conduct data exploration and variable selection.
6.
Prepare data analytic sandbox and perform extraction, loading and transformations.
7. Data science team investigates the problem and develop context to determine which resources to collect.

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