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    • Data Modeling

    Data Modeling Courses Online

    Learn data modeling techniques for structuring data. Understand how to create logical and physical data models for database design.

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    Explore the Data Modeling Course Catalog

    • G

      Google Cloud

      Google Workspace Mail Management - Français

      Skills you'll gain: Email Security, Data Loss Prevention, Google Workspace, Malware Protection, Security Controls, Personally Identifiable Information, Network Routing, Content Management, Record Keeping

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Vector Search and Embeddings - 简体中文

      Skills you'll gain: Large Language Modeling, Text Mining, Google Cloud Platform, Natural Language Processing, Information Architecture, Applied Machine Learning, Algorithms

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Master of Applied Data Science

      Skills you'll gain: Data Ethics, Data Storytelling, Database Design, Reinforcement Learning, Supervised Learning, Experimentation, PySpark, Interactive Data Visualization, Pandas (Python Package), Network Analysis, Deep Learning, Cloud Services, Natural Language Processing, JSON, Data Mining, Qualitative Research, Statistical Visualization, Unsupervised Learning, Applied Machine Learning, Time Series Analysis and Forecasting

      Earn a degree

      Degree · 1 - 4 Years

    • G

      Google Cloud

      Managing Google Workspace - Français

      Skills you'll gain: Google Workspace, Gmail, Cloud Management, Document Management, Data Management, Mobile Security, System Configuration, Identity and Access Management, Enterprise Application Management, Cloud Storage, Data Import/Export

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Transformer Models and BERT Model - Deutsch

      Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative AI, Artificial Neural Networks

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      G

      Google Cloud

      Introdução à análise de dados no Google Cloud

      Skills you'll gain:

      Beginner · Course · 1 - 3 Months

    • M

      Microsoft

      Data Manipulation and Transactions in SQL Server

      Skills you'll gain: Transaction Processing, Microsoft SQL Servers, Database Management, SQL, Data Manipulation, Relational Databases, Data Integrity, Generative AI, Performance Tuning

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Planning for a Google Workspace Deployment - Français

      Skills you'll gain: Data Migration, Change Management, Google Workspace, Organizational Change, User Provisioning, Application Deployment, Enterprise Application Management, Cloud Computing, End User Training and Support, Systems Integration, Employee Training

      Beginner · Course · 1 - 4 Weeks

    • B

      Ball State University

      Master of Science in Data Science

      Skills you'll gain:

      Earn a degree

      Degree · 1 - 4 Years

    • M

      Meta

      Introduction au Marketing des réseaux sociaux

      Skills you'll gain: Social Media Marketing, Social Media, Target Audience, Marketing, Social Media Strategy, Instagram, Customer Analysis, Marketing Channel, Marketing Strategies, Facebook, Digital Marketing, Key Performance Indicators (KPIs), Goal Setting

      Beginner · Course · 1 - 3 Months

    • S

      SkillUp EdTech

      E-commerce and Email Marketing

      Skills you'll gain:

      Intermediate · Course

    • G

      Google Cloud

      Responsible AI for Developers: Interpretability & Transparency - Français

      Skills you'll gain: Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, MLOps (Machine Learning Operations), Machine Learning, Machine Learning Methods

      Intermediate · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular data modeling courses

    • Google Workspace Mail Management - Français: Google Cloud
    • Vector Search and Embeddings - 简体中文: Google Cloud
    • Master of Applied Data Science: University of Michigan
    • Managing Google Workspace - Français: Google Cloud
    • Transformer Models and BERT Model - Deutsch: Google Cloud
    • Introdução à análise de dados no Google Cloud : Google Cloud
    • Data Manipulation and Transactions in SQL Server: Microsoft
    • Planning for a Google Workspace Deployment - Français: Google Cloud
    • Master of Science in Data Science: Ball State University
    • Introduction au Marketing des réseaux sociaux: Meta

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Data Modeling

    Data modeling is an essential prerequisite to proper database design, as it clearly establishes the structures, relationships, and flows of data through an organization. This diagramming is important because it ensures the integrity of a company’s data and its interrelationships in the database management system (DBMS) so that it can be relied on for accurate analysis.

    Data modeling has become more challenging in the big data era, as vast flows of unstructured, real-time data are not easily classified. However, there are also new tools available for data management professionals. Neo4j, one type of NoSQL database, can help with data modeling by filtering large datasets with graph analytics. And, with Apache Impala’s ability to analyze big data in the cloud, data modelers can create flexible system protocols that can evolve with data growth.‎

    Data modeling is a complex process that demands the ability to precisely understand and diagram business operations, data flows, and data management systems. Database administrators especially rely on data modeling to design and manage an organization’s databases to ensure security, integrity, and freedom from error.

    Data engineers also use data modeling skills to efficiently design and build an organization’s data infrastructure. They are responsible for creating the data pipelines, data warehouses, and data lakes used for business operations, exploratory data analysis, and predictive business intelligence. According to Glassdoor, the national average salary for a data engineer in the United States is $102,864 per year.‎

    Yes! Coursera offers a wide variety of online courses and Specializations in data modeling, as well as related topics like data warehousing, business intelligence, and big data. You can take courses from top-ranked institutions like the University of California San Diego and the University of Illinois at Urbana-Champaign, so you don’t have to sacrifice the quality of your education for the opportunity to learn online.

    Coursera also offers the opportunity to pursue a full Master of Science in Data Science degree from the University of Colorado Boulder. Whether you’re a data science beginner or adding new skills to your resume, data modeling will give you an essential perspective into the structure of an organization’s data operations.‎

    Previous experience or education—at the high school or postsecondary levels—in information science, applied mathematics, or computer science and related topics can help you form the foundation needed to learn about data modeling. A background in business management and information systems management may also be beneficial. Naturally, you'll need good basic computer skills, as well as some experience in areas like database administration, computer architecture, data representation, and digital logic. An understanding of modeling tools—like PowerDesigner, Erwin, and Enterprise Architect—can also prepare you to learn data modeling. Experience with database management systems is also a must. Software development experience can be helpful too.‎

    While technical skills are important for work that involves data modeling, you must also be a good communicator and teacher. In many cases, you'll have to explain your job to those who may not fully understand it. This means you'll need good written and verbal communication skills. It also means you'll need good interpersonal skills and the ability to work well with a team. You should also have a business-minded personality. The ideas and standards you implement will be based on the needs of the business where you work. You must be someone who can learn, change, and adapt quickly as you'll find that the job calls for that on many occasions.‎

    Anyone with a background and passion for math, data, and computers may find that learning data modeling is right for them, especially if you dream of working in the business world and helping companies reach their full potential. Your technical knowhow and communication skills must be equally as sharp if you want a career in the field. However, choosing a career in this field means plenty of job opportunities, a competitive salary, and a great outlook for the future. You must be willing to build on your education and experience to work your way up from a career such as a data analyst if you choose this path.‎

    Online Data Modeling courses offer a convenient and flexible way to enhance your knowledge or learn new Data Modeling skills. Choose from a wide range of Data Modeling courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Data Modeling, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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