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Vitthal Srinivasan
This course will teach you how to leverage Sisense data models - both ElastiCubes as well as live models - in order to pull together curated datasets for use in your Sisense dashboards.
Read more
This course will teach you how to leverage Sisense data models - both ElastiCubes as well as live models - in order to pull together curated datasets for use in your Sisense dashboards.
Read more
This course will teach you how to leverage Sisense data models - both ElastiCubes as well as live models - in order to pull together curated datasets for use in your Sisense dashboards.
Most large organizations will have data stored in different locations and formats, and these will often need to be brought together for meaningful analysis. In this course, Analyzing Data from Different Sources with Sisense, you’ll learn to load and combine data from several sources before analysis can be performed, and how to do this with both dominant data models in Sisense - ElastiCubes, as well as live models. First, you’ll explore the different types of sources from which data can be brought into Sisense. Next, you’ll discover various techniques to combine related data from different sources. Finally, you’ll learn how to work with live data in Sisense. When you’re finished with this course, you’ll have the skills and knowledge of connecting to and combining data from multiple sources needed to perform a thorough and all-round analysis of your business data using Sisense.
Register for this course and see more details by visiting:
OpenCourser.com/course/9vdctv/analyzing
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What's inside
Syllabus
Course Overview
Connecting to Different Data Sources
Combining Data from Multiple Sources
Working with Live Data
Read more
Syllabus
Course Overview
Connecting to Different Data Sources
Combining Data from Multiple Sources
Working with Live Data
Read more
Good to know
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Know what's good ,
what to watch for , and
possible dealbreakers
Teaches learners how to combine disparate datasets, developing skills relevant to real-world data analytics
Suitable for individuals seeking to advance their Sisense data analysis skills or gain foundational knowledge in data integration
Incorporates industry-standard practices, including ElastiCubes and live modeling, equipping learners with relevant techniques
Covers essential concepts of data integration and analysis, providing a solid foundation for further learning
Provides learners with opportunities to apply their skills through hands-on activities, enhancing practical understanding
Led by experienced industry professionals, ensuring the course content is up-to-date and relevant
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Save Analyzing Data from Different Sources with Sisense to your list so you can find it easily later:
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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 Analyzing Data from Different Sources with Sisense with these
activities:
Review Data Modeling Concepts
Show steps
Review the fundamental concepts of data modeling, including ElastiCubes and live models, to strengthen your understanding of the course material.
Browse courses on
Data Modeling
Show steps
-
Read articles and watch videos on data modeling
-
Review previous notes or coursework on data modeling
-
Practice creating simple data models
Compile a List of Sisense Resources
Show steps
Gather various resources related to Sisense, such as documentation, tutorials, and community forums, to enhance your learning experience and troubleshoot any issues.
Show steps
-
Search online for Sisense-related resources
-
Bookmark useful articles, videos, and websites
-
Organize the resources into a central location for easy access
Load and Combine Data from Multiple Sources
Show steps
Practice loading and combining data from multiple sources, using techniques covered in the course, to improve your understanding of data integration.
Show steps
-
Identify different data sources for a specific scenario
-
Load data from the identified sources using Sisense
-
Combine the loaded data using appropriate methods
-
Validate the combined data for accuracy and completeness
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Sisense User Group Meeting
Show steps
Engage with Sisense experts and share knowledge with other users by attending a user group meeting, to broaden your understanding of the platform.
Show steps
-
Locate and register for a Sisense User Group meeting in your area
-
Attend the meeting and participate in discussions
-
Network with fellow Sisense users and experts
Create a Dashboard Using Live Data
Show steps
Develop a dashboard using live data to demonstrate your understanding of real-time data analysis and visualization.
Show steps
-
Choose a relevant data source for your dashboard
-
Connect the data source to Sisense
-
Create a dashboard with visualizations to display live data
-
Configure alerts and notifications for the dashboard
Explore Advanced Features of Sisense
Show steps
Enhance your knowledge of Sisense by exploring advanced features such as calculated fields, custom widgets, and scripting, to extend the functionality of your dashboards.
Show steps
-
Review online documentation or watch tutorials on advanced Sisense features
-
Experiment with creating calculated fields and custom widgets
-
Write scripts to automate tasks within Sisense
Answer Questions on Sisense Forums
Show steps
Reinforce your understanding of Sisense by assisting others in online forums, answering questions, and sharing your knowledge with the community.
Show steps
-
Join Sisense online forums
-
Monitor the forums for questions related to the course topics
-
Provide clear and helpful answers to questions
Contribute to Sisense Open Source Projects
Show steps
Make a valuable contribution to the Sisense community by participating in open source projects, expanding your knowledge and supporting the platform's development.
Show steps
-
Identify a Sisense open source project to contribute to
-
Review the project's documentation and codebase
-
Make code contributions or provide documentation improvements
Review Data Modeling Concepts
Show steps
Review the fundamental concepts of data modeling, including ElastiCubes and live models, to strengthen your understanding of the course material.
Browse courses on
Data Modeling
Show steps
Show steps
Show steps
- Read articles and watch videos on data modeling
- Review previous notes or coursework on data modeling
- Practice creating simple data models
Compile a List of Sisense Resources
Show steps
Gather various resources related to Sisense, such as documentation, tutorials, and community forums, to enhance your learning experience and troubleshoot any issues.
Show steps
Show steps
Show steps
- Search online for Sisense-related resources
- Bookmark useful articles, videos, and websites
- Organize the resources into a central location for easy access
Load and Combine Data from Multiple Sources
Show steps
Practice loading and combining data from multiple sources, using techniques covered in the course, to improve your understanding of data integration.
Show steps
Show steps
Show steps
- Identify different data sources for a specific scenario
- Load data from the identified sources using Sisense
- Combine the loaded data using appropriate methods
- Validate the combined data for accuracy and completeness
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Sisense User Group Meeting
Show steps
Engage with Sisense experts and share knowledge with other users by attending a user group meeting, to broaden your understanding of the platform.
Show steps
Show steps
Show steps
- Locate and register for a Sisense User Group meeting in your area
- Attend the meeting and participate in discussions
- Network with fellow Sisense users and experts
Create a Dashboard Using Live Data
Show steps
Develop a dashboard using live data to demonstrate your understanding of real-time data analysis and visualization.
Show steps
Show steps
Show steps
- Choose a relevant data source for your dashboard
- Connect the data source to Sisense
- Create a dashboard with visualizations to display live data
- Configure alerts and notifications for the dashboard
Explore Advanced Features of Sisense
Show steps
Enhance your knowledge of Sisense by exploring advanced features such as calculated fields, custom widgets, and scripting, to extend the functionality of your dashboards.
Show steps
Show steps
Show steps
- Review online documentation or watch tutorials on advanced Sisense features
- Experiment with creating calculated fields and custom widgets
- Write scripts to automate tasks within Sisense
Answer Questions on Sisense Forums
Show steps
Reinforce your understanding of Sisense by assisting others in online forums, answering questions, and sharing your knowledge with the community.
Show steps
Show steps
Show steps
- Join Sisense online forums
- Monitor the forums for questions related to the course topics
- Provide clear and helpful answers to questions
Contribute to Sisense Open Source Projects
Show steps
Make a valuable contribution to the Sisense community by participating in open source projects, expanding your knowledge and supporting the platform's development.
Show steps
Show steps
Show steps
- Identify a Sisense open source project to contribute to
- Review the project's documentation and codebase
- Make code contributions or provide documentation improvements
Career center
Learners who complete Analyzing Data from Different Sources with Sisense will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. They use data visualization and reporting tools to summarize and present data in a way that is easy to understand. This course will help you develop the skills you need to combine data from different sources, analyze it, and create insightful visualizations.
Business Analyst
Business Analyst
Business Analysts work with businesses to improve their operations and decision-making. They use data analysis to identify opportunities for improvement and recommend solutions. This course will help you learn how to combine data from different sources to create insights that can help businesses make better decisions.
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems. They develop and build predictive models and machine learning algorithms to identify patterns and trends in data. This course will help you build a foundation in data analysis and visualization skills, which are essential for Data Scientists.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines that collect, clean, and store data. They work with data analysts and scientists to ensure that data is available and ready for analysis. This course will help you learn how to connect to different data sources and combine data from multiple sources.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. They ensure that data is stored securely and efficiently, and that it is available to authorized users. This course will help you learn how to connect to different data sources and combine data from multiple sources.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They use data analysis to understand user needs and to improve the performance of their applications. This course will help you develop the skills you need to combine data from different sources and to create insights that can help you build better software applications.
Financial Analyst
Financial Analyst
Financial Analysts use data to evaluate the financial performance of companies and to make investment recommendations. They use data visualization and reporting tools to summarize and present data in a way that is easy to understand. This course will help you develop the skills you need to combine data from different sources and to create insights that can help you make better investment decisions.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and trends. They use this information to help businesses develop marketing strategies and products. This course will help you learn how to combine data from different sources to create insights that can help you understand your target market.
Statistician
Statistician
Statisticians use data to collect, analyze, and interpret data. They develop and use statistical models to understand the relationships between different variables and to make predictions. This course will help you build a foundation in data analysis and visualization skills, which are essential for Statisticians.
Actuary
Actuary
Actuaries use data to assess risk and uncertainty. They develop and use mathematical models to predict future events and to calculate the probability of events occurring. This course will help you build a foundation in data analysis and visualization skills, which are essential for Actuaries.
Epidemiologist
Epidemiologist
Epidemiologists use data to investigate the causes and spread of diseases. They use data visualization and reporting tools to summarize and present data in a way that is easy to understand. This course will help you develop the skills you need to combine data from different sources and to create insights that can help you prevent and control diseases.
Health Services Manager
Health Services Manager
Health Services Managers plan, direct, and coordinate the delivery of health care services. They use data to evaluate the performance of health care programs and to make decisions about how to improve the quality of care. This course will help you learn how to combine data from different sources to create insights that can help you improve the health of your community.
Public Health Analyst
Public Health Analyst
Public Health Analysts use data to identify and address public health problems. They develop and implement programs to prevent and control diseases, and to promote health and well-being. This course will help you learn how to combine data from different sources to create insights that can help you improve the health of your community.
Social Worker
Social Worker
Social Workers help people mengatasi social and economic problems. They use data to assess the needs of their clients and to develop and implement programs to help them. This course will help you learn how to combine data from different sources to create insights that can help you improve the lives of your clients.
Teacher
Teacher
Teachers educate students and help them learn. They use data to assess the progress of their students and to develop and implement lesson plans. This course may be useful for Teachers who want to learn how to use data to improve their teaching practices.
For more career information including salaries, visit:
OpenCourser.com/course/9vdctv/analyzing
Reading list
We've selected 12 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
Analyzing Data from Different Sources with Sisense.
Save
Provides a comprehensive overview of data integration for business intelligence, including best practices for combining data from different sources. It valuable resource for anyone looking to learn more about how to use Sisense to analyze data from different sources.
Classic in the field of data warehousing. It provides a comprehensive overview of the design and implementation of data warehouses, including best practices for combining data from different sources. It valuable resource for anyone looking to learn more about how to use Sisense to analyze data from different sources.
Save
Provides a comprehensive overview of the fundamentals of data mining. It covers a variety of topics, including data mining techniques, data mining applications, and data mining tools. It valuable resource for anyone who wants to learn more about data mining.
Save
Provides a comprehensive overview of the fundamentals of machine learning. It covers a variety of topics, including machine learning algorithms, machine learning applications, and machine learning tools. It valuable resource for anyone who wants to learn more about machine learning.
Save
Provides a comprehensive overview of the fundamentals of deep learning. It covers a variety of topics, including deep learning architectures, deep learning algorithms, and deep learning applications. It valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of the fundamentals of reinforcement learning. It covers a variety of topics, including reinforcement learning algorithms, reinforcement learning applications, and reinforcement learning tools. It valuable resource for anyone who wants to learn more about reinforcement learning.
Provides a comprehensive overview of data in motion. It valuable resource for anyone looking to learn about the different ways to manage data in motion.
Provides a collection of patterns for integrating data from different sources. It valuable resource for anyone looking to learn about the different ways to integrate data.
Provides a collection of patterns for designing data warehouses. It valuable resource for anyone looking to learn about the different ways to design data warehouses.
Provides a comprehensive overview of data modeling techniques. It valuable resource for anyone looking to learn about the different ways to model data.
Provides a comprehensive overview of data quality. It valuable resource for anyone looking to learn about the different ways to improve data quality.
Provides a comprehensive overview of data governance. It valuable resource for anyone looking to learn about the different ways to implement data governance.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9vdctv/analyzing
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Time
59 hours
Level
Intermediate
Via
Pluralsight
Instructor
Vitthal Srinivasan
Language
English
Good to know
Teaches learners how to combine disparate datasets, developing skills relevant to real-world data analytics
Suitable for individuals seeking to advance their Sisense data analysis skills or gain foundational knowledge in data integration
Incorporates industry-standard practices, including ElastiCubes and live modeling, equipping learners with relevant techniques
Covers essential concepts of data integration and analysis, providing a solid foundation for further learning
Provides learners with opportunities to apply their skills through hands-on activities, enhancing practical understanding
Led by experienced industry professionals, ensuring the course content is up-to-date and relevant
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