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Sai Krishna

Understanding and Implementing Data Models in Sisense will make you comfortable in connecting to data sources and building data-model.

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Understanding and Implementing Data Models in Sisense will make you comfortable in connecting to data sources and building data-model.

In this course, Understanding and Implementing Data Models in Sisense, you’ll learn techniques to build data-model. First, you’ll explore connecting to various data sources. Next, you’ll discover combining data. Finally, you’ll learn how to apply data model techniques. When you’re finished with this course, you’ll have the skills and knowledge of data model needed to build elasticube.

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What's inside

Syllabus

Course Overview
Elasticube Model
Building Data Model
Creating Live Connection
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Administration

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for those new to or familiar with data modeling
Covers fundamentals and provides hands-on practice
Provides techniques that can be applied immediately
Prior experience with databases and Sisense may enhance learning

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Understanding and Implementing Data Models with Sisense with these activities:
Review data modeling concepts
Revisit the basics of data modeling to strengthen your foundational understanding before starting the course.
Browse courses on Data Modeling
Show steps
  • Review data modeling principles and techniques
  • Explore different types of data models
  • Practice creating simple data models
Participate in peer review sessions
Gain valuable feedback and insights by sharing your data models with peers and reviewing theirs.
Show steps
  • Connect with classmates or fellow learners.
  • Organize regular sessions to share and discuss data models.
  • Provide constructive feedback and suggestions for improvement.
Follow tutorials on data modeling techniques
Enhances understanding of data modeling techniques by providing guided practice and examples.
Browse courses on Data Modeling
Show steps
  • Identify and research data modeling techniques
  • Follow tutorial on a specific data modeling technique
Five other activities
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Show all eight activities
Participate in a peer study group or discussion forum
Fosters collaboration, knowledge sharing, and critical thinking among peers, enhancing understanding of course material.
Show steps
  • Join or create a peer study group
  • Discuss and exchange ideas on data modeling concepts
Practice connecting to data sources
Establish a solid foundation by practicing various data source connection techniques.
Browse courses on Data Sources
Show steps
  • Go through Sisense documentation on supported data sources.
  • Practice connecting to a variety of data sources including databases, files, and cloud services.
  • Try establishing live connections to databases.
Practice combining data and building data models
Strengthen your understanding of data modeling by practicing combining data and building different types of data models.
Browse courses on Data Models
Show steps
  • Review the principles of data modeling and different types of data models.
  • Practice combining data from multiple sources using different join types.
  • Build a star schema data model and a snowflake schema data model.
Create an elasticube model based on a real-world scenario
Provides an opportunity to apply data modeling knowledge to a realistic problem, deepening understanding and solidifying skills.
Browse courses on Data Modeling
Show steps
  • Identify a real-world scenario that requires data modeling
  • Design and create an elasticube model based on the scenario
  • Validate and refine the elasticube model
Start a personal project using Sisense
Enhance your practical skills by starting a personal project that involves using Sisense to solve a data-related problem or explore different data modeling techniques.
Show steps
  • Identify a project idea
  • Gather necessary resources
  • Plan and execute your project

Career center

Learners who complete Understanding and Implementing Data Models with Sisense will develop knowledge and skills that may be useful to these careers:
Business Intelligence Analyst
Business Intelligence Analysts collect and analyze data to develop insights that inform business decision-making. Though a background in computer science or business is usually required, Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Data Analyst
Data Analysts structure data for various data science projects and more. To become a Data Analyst, it is helpful to have a background in statistics and computer science. Understanding and Implementing Data Models with Sisense may be helpful to you because it can help you build a foundation in connecting to various data sources and building data models.
Data Scientist
Data Scientists develop, implement, and evaluate statistical and machine learning models to extract useful information and insights from data. While a PhD is usually required, Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in building data models.
Data Engineer
Data Engineers design, implement, and maintain data pipelines and databases to support data-driven applications. This role usually requires a bachelor’s degree in computer science or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in building data models.
Database Administrator
Database Administrators maintain and optimize databases to ensure high performance and availability. This role usually requires at least a bachelor’s degree in computer science or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in connecting to data sources.
Business Analyst
Business Analysts analyze business processes and identify areas for improvement. To become a Business Analyst, you usually need a bachelor's degree in business or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it can help build a foundation in connecting to data sources and building data models.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze financial data and make investment recommendations. This role usually requires a master's or doctoral degree in mathematics, statistics, or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Actuary
Actuaries assess and manage financial risks for insurance companies and other organizations. This role usually requires a bachelor's degree in mathematics, statistics, or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Market Researcher
Market Researchers conduct research to understand consumer needs and preferences. This role usually requires a bachelor’s degree in business, marketing, or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it can help build a foundation in data model techniques.
Data Visualization Analyst
Data Visualization Analysts create visual representations of data to communicate insights and trends. This role usually requires a bachelor’s degree in computer science, design, or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Operations Research Analyst
Operations Research Analysts use analytical methods to solve complex problems in business and industry. This role usually requires a master's or doctoral degree in operations research, industrial engineering, or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Statistician
Statisticians collect, analyze, interpret, and present data. This role usually requires a master's or doctoral degree in statistics or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Software Engineer
Software Engineers design, develop, and maintain software systems. This role usually requires a bachelor’s degree in computer science or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Financial Analyst
Financial Analysts provide investment advice and make investment recommendations to individuals and organizations. This role usually requires a bachelor’s degree in finance or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.
Risk Analyst
Risk Analysts identify, assess, and mitigate risks for businesses and organizations. This role usually requires a bachelor’s degree in finance, business, or a related field. Understanding and Implementing Data Models with Sisense may be helpful to you because it helps build a foundation in data model techniques.

Reading list

We've selected 17 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Understanding and Implementing Data Models with Sisense.
If you want to explore data modeling using Visio software, this book great option. It provides step-by-step instructions and examples.
Classic work on data warehouse design and implementation. It provides a comprehensive overview of the data warehouse architecture, as well as step-by-step instructions on how to design and implement a data warehouse.
Provides a practical introduction to conceptual data modeling and its applications in business.
Practical guide to dimensional modeling, the most widely used data modeling technique for data warehouses. It provides step-by-step instructions on how to design and implement a dimensional model.
Provides a practical guide to data modeling, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn more about how to design and implement data models.
Provides a concise overview of data modeling, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn the basics of data modeling.
Is an excellent resource for anyone interested in data modeling and database design. It covers a range of topics, including UML, ER modeling, and SQL.
Provides a comprehensive overview of data modeling patterns, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn more about how to design and implement data models using patterns.
Provides a concise overview of data modeling, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn the basics of data modeling.
Provides a practical guide to data modeling, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn more about how to design and implement data models.
Provides a comprehensive overview of data modeling, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn more about the theory and practice of data modeling.
Provides a comprehensive overview of data modeling for the enterprise, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn more about how to design and implement data models for the enterprise.
Provides a comprehensive overview of data modeling best practices, covering both conceptual and logical modeling. It valuable resource for anyone who wants to learn more about how to design and implement data models using best practices.
Provides a practical guide to database design and modeling techniques. It good resource for those who want to learn about the practical aspects of data modeling.

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