Roles and responsibilities: Data modeller designs, implements, and documents data architect and data modeling solutions that include use of dimensional, relational, and NoSQL databases. The solutions support enterprise information management, business intelligence, machine learning, data science, and other business-related fields. The responsibilities of the data modeller include implementing business and IT data requirements through new data strategies and designs, work with business application teams, define data modeling and design standards, tools, and practices for enterprise models, identifying the architecture and infrastructure, hands-on designing and modeling, working independently to address project requirements and challenges to reduce project risks.
Average salary (pPer annum): US$117,590
- Bachelors or master’s degree in computer/ data science or any related fields.
- Experience with data warehouse, enterprise big data platforms
- Skills of using RDBMS, NoSQL data platforms, and ETL
- Good knowledge of metadata management and data modeling
- Active team management and communication skills
Top 3 Online Courses:
Mastering Data Modelling Fundamentals (udemy): This course equips the learner with mastering the techniques needed to build data models for the organization. It helps the learner to build accurate data models consisting of entities, attributes, relationships, hierarchies, and modeling constructs. It teaches how to apply data modeling designs principles through classic entity-relationship notation and converting conceptual data models to logical and physical models.
Data modeling and relational database design using ERwin (udemy): The cournes courses help the learner to create entity relationships diagrams by identifying entities, attributes, relationships, and constraints. It supports in developing sound database designs by applying proven data modeling techniques, optimizing the relational database design for various functional requirements.
Data Modeling (Harvard Extension School): The course teaches data modeling methodologies with the aim of understanding how to choose, apply and interpret appropriate statistical designs and analysis for practical problems with regard to data issues. The course covers non-linear regression models, model building steps, diagnostic of models, and remedial measures.
Top 3 Educational Institutes Offering the Program With degree:
- Bachelor’s in Computer Science along with Data Science and Economics: Massachusetts Institute of Technology.
- Bachelor’s in Data Science: ESSEC and CentraleSupelec.
- Bachelor’s and MastersMaster’s in Data Science: IE Spain
Top 5 Recruiters for This Job:
Deloitte: Deloitte is a leading provider of audit and assurance, consultancy, financial advisory, and tax services, and etc. This information is stored in the form of data and so data engineers are needed for the company for maintaining the organization’s whole data ecosystem, this includes data sources and databases to data storage solutions.
Capgemini: Capgemini is a consulting, technology services, and digital transformation company with data used for defining the end of the database, and then formulates the organizational data strategy, including standards of data quality, the flow of data within the organization, and security of the data.
Fractal Analytics: The company has emerged as one of the top analytics services providers in the country. The company has a global footprint boasting of several Fortune 500 companies from industries like retail, insurance, and technology. It has many branches in all parts of India hiring new positions.
Amazon: Amazon is one of the biggest e-commerce companies around the world and is also among the top data recruiters worldwide. Amazon is a giant of data and to comprehend the intensity of data it requires data engineers for its core operations from marketing streamlining, logistics, and inventory management to sales expectation and even HR analytics.
Bank of America: It is an American American multinational bank that relies on huge amounts of data architects for building complex computer database systems that are accessible, useful, and secure the processes of the bank and its data by understanding the business need and exploring the existing data structure.
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