VOOZH about

URL: https://www.coursera.org/learn/database-to-ai-practical-data-analytics-integration

⇱ Database to AI: Practical Data Analytics Integration | Coursera


Database to AI: Practical Data Analytics Integration

Ends soon! Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.

Database to AI: Practical Data Analytics Integration

Included with

β€’

Learn more

Ask Coursera

Gain insight into a topic and learn the fundamentals.
9 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
9 hours to complete
Flexible schedule
Learn at your own pace

There are 4 modules in this course

This course introduces the fundamental concepts and emerging technologies in database design and modeling, database systems, data storage, and data governance. It presents a balanced theory-practice focus and covers entity relationship model and UML model, relational model, relational databases, Structured Query Language, and two flavors of NoSQL databases in MongoDB and Neo4j graph database. It also includes a brief introduction to big data management including hadoop, MapReduce, and Apache Spark. This course provides the theory and applications of database management to support data analytics, data mining, machine learning, and artificial intelligence.

In this module, you'll explore the foundational principles of database management, focusing on the differences between file-based and database approaches to data management. You will learn about the key elements of a database system and the advantages of using database management systems (DBMS) to organize, store, and manipulate data. Through this module, you'll develop skills in database design and administration, gaining a deeper understanding of how DBMS enhances data management and supports professional work in fields like data analytics.

What's included

3 videos7 readings2 assignments2 discussion prompts

3 videosβ€’Total 8 minutes
  • Course Introductionβ€’2 minutes
  • Meet Your Facultyβ€’2 minutes
  • File-Based vs. Database Approach to Data Managementβ€’5 minutes
7 readingsβ€’Total 41 minutes
  • Course Overviewβ€’1 minute
  • Syllabus - Database to AI: Practical Data Analytics Integrationβ€’10 minutes
  • Academic Integrityβ€’1 minute
  • The Power of Data: From Storage to Analyticsβ€’5 minutes
  • Transitioning from File-Based to Database Systemsβ€’8 minutes
  • Understanding Database Models and Architectureβ€’15 minutes
  • Module 1 Summaryβ€’1 minute
2 assignmentsβ€’Total 36 minutes
  • Check Your Prior Knowledgeβ€’6 minutes
  • Quiz 1β€’30 minutes
2 discussion promptsβ€’Total 120 minutes
  • Meet Your Fellow Learnersβ€’60 minutes
  • Data Management and Data Analyticsβ€’60 minutes

This module covers the architecture and categorization of Database Management Systems (DBMS). Here, you will learn the key components of DBMS architecture, including the query processor and storage manager, and how they interact to manage data. You will also learn to categorize DBMSs based on factors like data models, architecture, and usage, highlighting their characteristics and real-world applications. This module also provides resources and prompts for discussion to deepen understanding of DBMS types and their use cases in data management.

What's included

5 readings2 assignments1 discussion prompt

5 readingsβ€’Total 100 minutes
  • Components and Architecture of a DBMSβ€’20 minutes
  • Exploring DBMS Structure and Architectureβ€’54 minutes
  • Classifying DBMS: Models, Architectures, and Usesβ€’10 minutes
  • Understanding Data Models and Database Typesβ€’15 minutes
  • Module 2 Summaryβ€’1 minute
2 assignmentsβ€’Total 34 minutes
  • Check Your Prior Knowledgeβ€’4 minutes
  • Quiz 2β€’30 minutes
1 discussion promptβ€’Total 60 minutes
  • Data Management and Data Analyticsβ€’60 minutes

In this module, you'll explore the foundational steps of database design, focusing on conceptual data modeling using the Entity Relationship (ER) model. You will learn how to gather business requirements, identify key entity and relationship types, and develop a conceptual data model. This model serves as the blueprint for database design before transitioning to logical and physical designs. You'll also examine the limitations of the ER model and how to address them. By the end of this module, you will understand how to translate real-world business processes into a clear, organized conceptual data model.

What's included

1 video5 readings2 assignments

1 videoβ€’Total 6 minutes
  • Designing ER Models: Key Concepts and Applicationsβ€’6 minutes
5 readingsβ€’Total 33 minutes
  • Steps in Designing a Database: From Business Process to Implementationβ€’10 minutes
  • Designing ER Models: Key Concepts and Applicationsβ€’2 minutes
  • Ternary Relationship Typesβ€’10 minutes
  • ER Modeling in Practiceβ€’10 minutes
  • Module 3 Summaryβ€’1 minute
2 assignmentsβ€’Total 36 minutes
  • Check Your Prior Knowledgeβ€’6 minutes
  • Quiz 3β€’30 minutes

In this module we will learn three additional semantic data modeling concepts: specialization/generalization, categorization, and aggregation. These concepts enhance and extend the ER model discussed in the previous module. We will introduce an alternative conceptual model: the Unified Modeling Language (UML) class diagram. The UML is a modeling language that assists in the specification, visualization, construction, and documentation of artifacts of a software system. The UML can offer case diagrams, sequence diagrams, package diagrams, and deployment diagrams, etc. Here we use the UML for conceptual data modeling.

What's included

1 video6 readings2 assignments

1 videoβ€’Total 5 minutes
  • Data Modeling: UML Class Diagramβ€’5 minutes
6 readingsβ€’Total 24 minutes
  • Specialization and Generalizationβ€’5 minutes
  • Categorizationβ€’4 minutes
  • Aggregationβ€’3 minutes
  • UML Class Diagrams for Conceptual Data Modelingβ€’10 minutes
  • Module 4 Summaryβ€’1 minute
  • Congratulationsβ€’1 minute
2 assignmentsβ€’Total 36 minutes
  • Check Your Prior Knowledgeβ€’6 minutes
  • Quiz 4β€’30 minutes

Instructor

Northeastern University
8 Coursesβ€’1,209 learners

Explore more from Data Analysis

Why people choose Coursera for their career

πŸ‘ Image

Felipe M.

Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
πŸ‘ Image

Jennifer J.

Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
πŸ‘ Image

Larry W.

Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
πŸ‘ Image

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,