What is data modeling, and why is it important to learn about?

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.

What kinds of careers can I have with skills in data modeling?

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.

Can I learn about data modeling by taking online courses on Coursera?

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.

What skills or experience do I need to already have before learning data modeling?

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.

What kind of people are best suited for work that involves data modeling?

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.

How do I know if learning data modeling is right for me?

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.

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University of Colorado Boulder
Master of Science in Data Science
Compétences que vous acquerrez : Theoretical Computer Science, Probability & Statistics, General Statistics, Algorithms, Data Management, Mathematics, Strategy and Operations, Computer Architecture, Databases, Leadership and Management, Communication, Hardware Design, Statistical Programming, Operating Systems, Machine Learning, Research and Design, Data Analysis, Finance, Computer Programming, SQL, Writing, Regression, Business Analysis, Data Structures, Project Management, Software Engineering, Business Communication, Probability Distribution, Entrepreneurship, Database Design, Statistical Tests, Computer Graphics, Computer Networking, Design and Product, Statistical Analysis, Accounting, Systems Design, Human Computer Interaction, Data Model, Database Administration, Database Application, Database Theory, Machine Learning Algorithms, Statistical Machine Learning, PostgreSQL, Estimation, Data Visualization, Problem Solving, Operations Research, Internet Of Things, Network Architecture, Applied Mathematics, Computer Vision, Graph Theory, Deep Learning, Geometry, Security Engineering, User Experience, Marketing, Computer Graphic Techniques, Mathematical Theory & Analysis, Programming Principles, Python Programming, Supply Chain and Logistics, Algebra, Cryptography, Business Psychology, Interactive Design, Critical Thinking, Data Mining, Correlation And Dependence, Distributed Computing Architecture, Financial Analysis, Linear Algebra, Linux, User Experience Design, Cost Accounting, Differential Equations, Cloud Computing, Cyberattacks, Security Strategy, Computer Programming Tools, Computational Logic, Scrum (Software Development), Applied Machine Learning, Budget Management, Calculus, Econometrics, Experiment, Feature Engineering, Graphic Design, Other Programming Languages, Sales, Software Architecture, Software Testing, System Programming, Visual Design, Artificial Neural Networks, Emotional Intelligence, Market Analysis, NoSQL, Statistical Visualization, Data Warehousing, Strategy, Basic Descriptive Statistics, Computational Thinking, Data Analysis Software, Exploratory Data Analysis, Investment Management, Material Handling, Organizational Development, Product Lifecycle, Risk Management, Amazon Web Services, Big Data, Cloud Platforms, Culture, Decision Making, Graphics Software, Human Resources, Microarchitecture, Application Development, Computer Security Models, Network Model, Operational Analysis, Product Design, Reinforcement Learning, Software Security, System Security, User Research, Plot (Graphics), R Programming, Account Management, Banking, BlockChain, Business Process Management, C Programming Language Family, Data Architecture, FinTech, Financial Accounting, Financial Management, Geovisualization, Inventory Management, Management Accounting, Markov Model, Matlab, Natural Language Processing, Operations Management, Planning, Product Management, Spreadsheet Software, Storytelling, Supplier Relationship Management, Computer Science, Computer Security Incident Management, Data Science, Dimensionality Reduction, Forecasting, Journalism, Leadership Development, Network Analysis, Network Security, System Software
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University of Illinois
Graduate Certificate in Accounting Data Analytics
Compétences que vous acquerrez : Accounting, Finance, Leadership and Management, Business Analysis, Data Analysis, Entrepreneurship, Financial Accounting, Marketing, Strategy and Operations, Strategy, Sales, Financial Analysis, Communication, Management Accounting, Mergers & Acquisitions, Taxes, Probability & Statistics, Business Psychology, Statistical Programming, Investment Management, Research and Design, Audit, Generally Accepted Accounting Principles (GAAP), Marketing Management, Python Programming, Banking, Market Analysis, Human Resources, Basic Descriptive Statistics, Data Visualization, Market Research, Organizational Development, Statistical Analysis, Corporate Accouting, General Accounting, General Statistics, Customer Analysis, Machine Learning, Budget Management, Supply Chain and Logistics, Exploratory Data Analysis, Financial Management, Project Management, Culture, Marketing Design, Media Strategy & Planning, R Programming, Risk Management, Cost Accounting, Regression, Data Management, Business Communication, Business Development, Digital Marketing, Leadership Development, Operations Management, Spreadsheet Software, Accounts Payable and Receivable, Computer Programming, Advertising, Brand Management, Decision Making, Media Production, Design and Product, Negotiation, Product Marketing, Theoretical Computer Science, Data Visualization Software, Plot (Graphics), Algorithms, Data Analysis Software, Entrepreneurial Finance, Machine Learning Algorithms, Software Engineering, Statistical Tests, Performance Management, Data Structures, Inventory Management, Statistical Visualization, Adaptability, Advertising Sales, Big Data, Collaboration, Data Mining, Forecasting, Influencing, Natural Language Processing, Social Media, Software Testing, Storytelling, Databases, Experiment, Mathematics, Regulations and Compliance, SQL, Agile Software Development, Behavioral Economics, BlockChain, Business Design, Business Process Management, Change Management, Conflict Management, Creativity, Extract, Transform, Load, Graph Theory, Human Learning, Innovation, Marketing Psychology, Material Handling, Network Analysis, People Development, Planning, Problem Solving, Product Lifecycle, Public Relations, Search Engine Optimization, Securities Sales, Supply Chain Systems, Survey Creation, Web Design, Web Development, Probability Distribution, Cash Management, Correlation And Dependence, Critical Thinking, Database Administration, Microsoft Excel, Process Analysis, Visualization (Computer Graphics), Back-End Web Development, Business Intelligence, Computer Graphics, Data Architecture, Econometrics, Game Theory, Human Computer Interaction, Journalism, Operating Systems, Product Management, Scrum (Software Development), Systems Design, Tableau Software, User Research, Virtual Reality
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University of Colorado Boulder
Data Science Graduate Certificate
Compétences que vous acquerrez : Probability & Statistics, General Statistics, Regression, Machine Learning, Data Analysis, Statistical Tests, Theoretical Computer Science, Probability Distribution, Machine Learning Algorithms, Data Management, Statistical Analysis, Statistical Machine Learning, Business Analysis, Mathematics, Data Mining, Deep Learning, Python Programming, Statistical Programming, Artificial Neural Networks, Applied Machine Learning, Data Warehousing, Correlation And Dependence, Econometrics, Experiment, Algorithms, Reinforcement Learning, Calculus, Estimation, Exploratory Data Analysis, Basic Descriptive Statistics, Differential Equations, Feature Engineering, Natural Language Processing, Spreadsheet Software, Communication, Data Science, Data Structures, Dimensionality Reduction, Linear Algebra, Marketing, R Programming, SQL
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Graduate Certificate · 6-12 Months
Meta
Meta Database Engineer
Compétences que vous acquerrez : Statistical Programming, SQL, Databases, Computer Programming, Python Programming, Software Engineering, Programming Principles, Software Engineering Tools, Data Management, Database Application, Software Testing, Theoretical Computer Science, Computer Programming Tools, Database Administration, Data Structures, Database Design, Javascript, Software Architecture, Web Development, Accounting, Algorithms, Application Development, Applied Machine Learning, Business Analysis, Collaboration, Communication, Computer Science, Data Analysis, Data Model, Data Warehousing, Database Theory, Django (Web Framework), Entrepreneurship, Exploratory Data Analysis, Financial Analysis, Human Computer Interaction, Journalism, Leadership and Management, Linux, Machine Learning, Market Research, Mathematics, Operating Systems, Operations Research, Other Programming Languages, Probability & Statistics, Project Management, Research and Design, Strategy and Operations, User Experience
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Recherches liées à data modeling

data modeling and regression analysis in business

big data modeling and management systems

advanced data modeling

calculus through data & modeling: limits & derivatives

calculus through data & modeling: applying differentiation

calculus through data & modeling: differentiation rules

calculus through data & modeling: precalculus review

modeling data in the tidyverse

En résumé, voici 10 de nos cours data modeling les plus populaires

Calculus through Data & Modeling: Precalculus Review: Johns Hopkins University
Big Data Modeling and Management Systems: University of California San Diego
Calculus through Data & Modeling: Limits & Derivatives: Johns Hopkins University
Advanced Data Modeling: Meta
Calculus through Data & Modeling: Differentiation Rules: Johns Hopkins University
Calculus through Data & Modeling: Applying Differentiation: Johns Hopkins University
Data Modeling and Regression Analysis in Business: University of Illinois at Urbana-Champaign
Master of Science in Applied Data Analytics: Queen Mary, University of London
Master of Science in Data Science: University of Colorado Boulder
Graduate Certificate in Accounting Data Analytics: University of Illinois

Compétences que vous avez acquises en Machine Learning

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Deep Learning (30)

Réseau De Neurones Artificiels (24)

Big Data (18)

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Apprentissage Par Renforcement (13)

Algèbre (10)

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Algèbre Linéaire (10)

Régression Linéaire (9)

NumPy (9)

Questions fréquentes sur Modélisation des données

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.‎

Le contenu de cette FAQ a été mis à disposition à des fins d'information uniquement. Il est conseillé aux étudiants d'effectuer des recherches supplémentaires afin de s'assurer que les cours et autres qualifications suivis correspondent à leurs objectifs personnels, professionnels et financiers.