Podcast
Questions and Answers
Which team is responsible for setting up and further developing the Data Vault 2.0 reference architecture?
Which team is responsible for setting up and further developing the Data Vault 2.0 reference architecture?
- C-level executives
- Data scientists
- Power users
- Data warehouse team (correct)
What is the goal of managed self-service BI?
What is the goal of managed self-service BI?
- To limit access to data and information
- To automate decision-making processes
- To rely on gut-feeling for decision-making
- To transform organizations into data-driven organizations (correct)
What is one of the major use cases supported by managed self-service BI?
What is one of the major use cases supported by managed self-service BI?
- Developing custom-built solutions (correct)
- Automating decision-making processes
- Relying on gut-feeling for decision-making
- Limiting access to data and information
What concept is used to transform organizations into data-driven organizations?
What concept is used to transform organizations into data-driven organizations?
Why is it important to turn decisions into rational decisions by educated decision-makers?
Why is it important to turn decisions into rational decisions by educated decision-makers?
Which architecture concept is Managed Self-Service BI based on?
Which architecture concept is Managed Self-Service BI based on?
What is the purpose of the user space in Managed Self-Service BI?
What is the purpose of the user space in Managed Self-Service BI?
What are some best practices recommended for power users in the user space?
What are some best practices recommended for power users in the user space?
What is one of the issues with pure 'self-service BI'?
What is one of the issues with pure 'self-service BI'?
What is the purpose of the fences mentioned in the text?
What is the purpose of the fences mentioned in the text?
Which artifacts are used by power users to extend the solution in the data analytics platform?
Which artifacts are used by power users to extend the solution in the data analytics platform?
What is the purpose of user marts in the data analytics platform?
What is the purpose of user marts in the data analytics platform?
What is the advantage of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is the advantage of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is a challenge of self-service BI in terms of maintaining auditability?
What is a challenge of self-service BI in terms of maintaining auditability?
How do more advanced users in the BI dashboarding software customize their dashboards?
How do more advanced users in the BI dashboarding software customize their dashboards?
Which type of key is used for employees in the user spaces at Scalefree?
Which type of key is used for employees in the user spaces at Scalefree?
What is the main advantage of the user space on the data analytics platform?
What is the main advantage of the user space on the data analytics platform?
What is the purpose of monitoring the user spaces in managed self-service BI?
What is the purpose of monitoring the user spaces in managed self-service BI?
What happens when a solution in the user space exceeds a defined threshold in managed self-service BI?
What happens when a solution in the user space exceeds a defined threshold in managed self-service BI?
What is the goal of the industrialization effort in managed self-service BI?
What is the goal of the industrialization effort in managed self-service BI?
What is the purpose of adding a footnote to standard reports?
What is the purpose of adding a footnote to standard reports?
What is the role of Managed Self-Service BI in organizations?
What is the role of Managed Self-Service BI in organizations?
What can power users do with the footnotes in reports?
What can power users do with the footnotes in reports?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What is the role of Scalefree International GmbH?
What is the role of Scalefree International GmbH?
What is an indicator that a solution is stable and maybe just done?
What is an indicator that a solution is stable and maybe just done?
What is the primary issue faced by the business user mentioned in the text?
What is the primary issue faced by the business user mentioned in the text?
What is one way to extend existing standard solutions according to the text?
What is one way to extend existing standard solutions according to the text?
What is the purpose of using managed self-service BI for prototyping according to the text?
What is the purpose of using managed self-service BI for prototyping according to the text?
What is the advantage of rebuilding a stable solution using standard development techniques in the IT controlled area?
What is the advantage of rebuilding a stable solution using standard development techniques in the IT controlled area?
Which team is responsible for setting up and further developing the Data Vault 2.0 reference architecture?
Which team is responsible for setting up and further developing the Data Vault 2.0 reference architecture?
What is the purpose of using managed self-service BI for prototyping according to the text?
What is the purpose of using managed self-service BI for prototyping according to the text?
What is the advantage of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is the advantage of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What concept is used to transform organizations into data-driven organizations?
What concept is used to transform organizations into data-driven organizations?
What is the purpose of the user space in Managed Self-Service BI?
What is the purpose of the user space in Managed Self-Service BI?
What is one of the major use cases supported by managed self-service BI?
What is one of the major use cases supported by managed self-service BI?
What is the purpose of the fences mentioned in the text?
What is the purpose of the fences mentioned in the text?
What is a challenge of self-service BI in terms of maintaining auditability?
What is a challenge of self-service BI in terms of maintaining auditability?
What is the primary issue faced by the business user mentioned in the text?
What is the primary issue faced by the business user mentioned in the text?
What is the purpose of user marts in the data analytics platform?
What is the purpose of user marts in the data analytics platform?
What is the main advantage of the user space on the data analytics platform?
What is the main advantage of the user space on the data analytics platform?
What is the purpose of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is the purpose of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is one of the issues with pure 'self-service BI'?
What is one of the issues with pure 'self-service BI'?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
Which team is responsible for setting up and further developing the Data Vault 2.0 reference architecture?
Which team is responsible for setting up and further developing the Data Vault 2.0 reference architecture?
What is the primary purpose of adding a footnote to standard reports?
What is the primary purpose of adding a footnote to standard reports?
What is the main advantage of the user space on the data analytics platform?
What is the main advantage of the user space on the data analytics platform?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What is the additional benefit of combining the user space with the Data Vault 2.0 model?
What is the purpose of monitoring the user spaces in managed self-service BI?
What is the purpose of monitoring the user spaces in managed self-service BI?
What is the purpose of the user space in Managed Self-Service BI?
What is the purpose of the user space in Managed Self-Service BI?
What is the advantage of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is the advantage of using the artifacts provided by the Data Vault 2.0 architecture in data science?
What is the primary issue faced by the business user mentioned in the text?
What is the primary issue faced by the business user mentioned in the text?
What happens when a solution in the user space exceeds a defined threshold in managed self-service BI?
What happens when a solution in the user space exceeds a defined threshold in managed self-service BI?
What is the role of Scalefree International GmbH?
What is the role of Scalefree International GmbH?
Which of the following is NOT a benefit of the user space in the data analytics platform?
Which of the following is NOT a benefit of the user space in the data analytics platform?
What is the primary purpose of monitoring the user spaces in managed self-service BI?
What is the primary purpose of monitoring the user spaces in managed self-service BI?
What is the goal of the industrialization effort in managed self-service BI?
What is the goal of the industrialization effort in managed self-service BI?
What is the purpose of the "smart" business keys used at Scalefree?
What is the purpose of the "smart" business keys used at Scalefree?
What is a challenge of using spreadsheets for data analytics in managed self-service BI?
What is a challenge of using spreadsheets for data analytics in managed self-service BI?
Managed self-service BI is used to transform organizations into a data-driven organization.
Managed self-service BI is used to transform organizations into a data-driven organization.
The goal of managed self-service BI is to make data and information widely available to any decision-maker.
The goal of managed self-service BI is to make data and information widely available to any decision-maker.
Power users and data scientists drive the infrastructure and capabilities provided by the data warehouse team.
Power users and data scientists drive the infrastructure and capabilities provided by the data warehouse team.
Managed self-service BI supports the use case of power users who want to extend the data analytics platform with custom-built solutions.
Managed self-service BI supports the use case of power users who want to extend the data analytics platform with custom-built solutions.
The decision-making process in organizations is often based on rational decisions made by educated decision-makers.
The decision-making process in organizations is often based on rational decisions made by educated decision-makers.
Power users can extend the solution by additional data not integrated by the data warehouse team.
Power users can extend the solution by additional data not integrated by the data warehouse team.
Self-service BI allows power users and data scientists to access data sources directly and build their own solutions.
Self-service BI allows power users and data scientists to access data sources directly and build their own solutions.
Providing re-usable code libraries is a solution to avoid power users reinventing the same business logic and transformation logic.
Providing re-usable code libraries is a solution to avoid power users reinventing the same business logic and transformation logic.
Power users and data scientists have to deal with reducing or deleting personal data when required in self-service BI.
Power users and data scientists have to deal with reducing or deleting personal data when required in self-service BI.
Managed self-service BI architecture distinguishes between power users and casual users.
Managed self-service BI architecture distinguishes between power users and casual users.
Managed Self-Service BI is a concept based on the Data Vault 2.0 architecture and extends it by user space.
Managed Self-Service BI is a concept based on the Data Vault 2.0 architecture and extends it by user space.
Power users in the user space can build their own solutions using binary data that should not be loaded into a relational database.
Power users in the user space can build their own solutions using binary data that should not be loaded into a relational database.
The user space in Managed Self-Service BI is similar to sandboxing in other self-service approaches, but with a time limitation.
The user space in Managed Self-Service BI is similar to sandboxing in other self-service approaches, but with a time limitation.
In Managed Self-Service BI, power users have the freedom to do whatever they want in the user space without any guidelines.
In Managed Self-Service BI, power users have the freedom to do whatever they want in the user space without any guidelines.
The user space in Managed Self-Service BI is a green field where power users can create their own solutions without any limitations.
The user space in Managed Self-Service BI is a green field where power users can create their own solutions without any limitations.
Managed Self-Service BI is a pattern that works well with organizations driven by the business.
Managed Self-Service BI is a pattern that works well with organizations driven by the business.
The user space in the data analytics platform allows power users to create dimensions.
The user space in the data analytics platform allows power users to create dimensions.
Adding a footnote to standard reports helps casual users distinguish between standard reports and power user reports.
Adding a footnote to standard reports helps casual users distinguish between standard reports and power user reports.
Data Vault 2.0 helps organizations make data widely available while maintaining security and privacy.
Data Vault 2.0 helps organizations make data widely available while maintaining security and privacy.
Scalefree International GmbH is a Big-Data consulting firm in Europe.
Scalefree International GmbH is a Big-Data consulting firm in Europe.
True or false: The industrialization of a solution becomes easier when a power user stops executing DDL statements on their user space.
True or false: The industrialization of a solution becomes easier when a power user stops executing DDL statements on their user space.
True or false: Power users are usually eager to maintain the solutions they have built.
True or false: Power users are usually eager to maintain the solutions they have built.
True or false: The primary purpose of managed self-service BI is to prototype and generate revenues from business prototypes.
True or false: The primary purpose of managed self-service BI is to prototype and generate revenues from business prototypes.
True or false: Power users can extend existing standard solutions by creating new computed satellites in their user space.
True or false: Power users can extend existing standard solutions by creating new computed satellites in their user space.
True or false: The user-defined satellites created by power users in the user space can be used to create custom dimensions in the information marts.
True or false: The user-defined satellites created by power users in the user space can be used to create custom dimensions in the information marts.
True or false: The user space on the data analytics platform allows for monitoring the adherence of guidelines by power users.
True or false: The user space on the data analytics platform allows for monitoring the adherence of guidelines by power users.
True or false: It is easier to query the information schema of the database than to retrieve the GRANTS to the entities in the user space.
True or false: It is easier to query the information schema of the database than to retrieve the GRANTS to the entities in the user space.
True or false: Creating many guidelines and regulations on how to use the user space limits the potential applications for the user spaces.
True or false: Creating many guidelines and regulations on how to use the user space limits the potential applications for the user spaces.
True or false: Managed self-service BI should only be used for solutions with high impact on the organization.
True or false: Managed self-service BI should only be used for solutions with high impact on the organization.
True or false: Industrialization monitoring helps identify solutions that exceed defined thresholds in terms of impact, stability, security violations, and resource consumption.
True or false: Industrialization monitoring helps identify solutions that exceed defined thresholds in terms of impact, stability, security violations, and resource consumption.
Managed self-service BI is used to transform organizations into a data-driven organization.
Managed self-service BI is used to transform organizations into a data-driven organization.
Power users and data scientists have to deal with reducing or deleting personal data when required in self-service BI.
Power users and data scientists have to deal with reducing or deleting personal data when required in self-service BI.
The user space in Managed Self-Service BI is similar to sandboxing in other self-service approaches, but with a time limitation.
The user space in Managed Self-Service BI is similar to sandboxing in other self-service approaches, but with a time limitation.
Power users can extend existing standard solutions by creating new computed satellites in their user space.
Power users can extend existing standard solutions by creating new computed satellites in their user space.
Power users are usually eager to maintain the solutions they have built.
Power users are usually eager to maintain the solutions they have built.
Power users can create their own information marts, called user marts, and create their own dashboards.
Power users can create their own information marts, called user marts, and create their own dashboards.
The artifacts provided by the Data Vault 2.0 architecture can be used to augment data flows with additional raw data.
The artifacts provided by the Data Vault 2.0 architecture can be used to augment data flows with additional raw data.
Managed Self-Service BI distinguishes between power users and casual users.
Managed Self-Service BI distinguishes between power users and casual users.
Power users and data scientists have to deal with reducing or deleting personal data when required, to secure the local datasets when sharing with their peers and to maintain auditability.
Power users and data scientists have to deal with reducing or deleting personal data when required, to secure the local datasets when sharing with their peers and to maintain auditability.
The user space in Managed Self-Service BI allows power users to create their own solutions without any limitations.
The user space in Managed Self-Service BI allows power users to create their own solutions without any limitations.
True or false: The user space in Managed Self-Service BI is limited to the relational database only.
True or false: The user space in Managed Self-Service BI is limited to the relational database only.
True or false: Power users in the user space can build their own solutions using binary data that should not be loaded into a relational database.
True or false: Power users in the user space can build their own solutions using binary data that should not be loaded into a relational database.
True or false: Power users can extend the solution by additional data not integrated by the data warehouse team.
True or false: Power users can extend the solution by additional data not integrated by the data warehouse team.
True or false: The primary purpose of monitoring the user spaces in managed self-service BI is to ensure adherence to data security and privacy guidelines.
True or false: The primary purpose of monitoring the user spaces in managed self-service BI is to ensure adherence to data security and privacy guidelines.
True or false: The user marts in the data analytics platform are part of the user space.
True or false: The user marts in the data analytics platform are part of the user space.
True or false: The user space on the data analytics platform allows power users to monitor the adherence of guidelines.
True or false: The user space on the data analytics platform allows power users to monitor the adherence of guidelines.
True or false: Managed self-service BI should only be used for solutions with relatively low impact on the organization.
True or false: Managed self-service BI should only be used for solutions with relatively low impact on the organization.
True or false: Industrialization in managed self-service BI involves analyzing and redesigning solutions in the user space.
True or false: Industrialization in managed self-service BI involves analyzing and redesigning solutions in the user space.
True or false: Monitoring the user spaces helps identify solutions that exceed defined thresholds in terms of impact, stability, security, and resource consumption.
True or false: Monitoring the user spaces helps identify solutions that exceed defined thresholds in terms of impact, stability, security, and resource consumption.
True or false: The goal of the industrialization effort is to reimplement solutions from the user space in the IT controlled area of the data analytics platform.
True or false: The goal of the industrialization effort is to reimplement solutions from the user space in the IT controlled area of the data analytics platform.
Managed Self-Service BI is a pattern that works well with organizations driven by the business.
Managed Self-Service BI is a pattern that works well with organizations driven by the business.
Data Vault 2.0 helps organizations make data widely available while maintaining security and privacy.
Data Vault 2.0 helps organizations make data widely available while maintaining security and privacy.
Power users in the user space can build their own solutions using binary data that should not be loaded into a relational database.
Power users in the user space can build their own solutions using binary data that should not be loaded into a relational database.
Adding a footnote to standard reports helps casual users distinguish between standard reports and power user reports.
Adding a footnote to standard reports helps casual users distinguish between standard reports and power user reports.
Scalefree International GmbH is a Big-Data consulting firm in Europe.
Scalefree International GmbH is a Big-Data consulting firm in Europe.
True or false: The user space in Managed Self-Service BI is a sandbox where power users can create their own solutions without any limitations.
True or false: The user space in Managed Self-Service BI is a sandbox where power users can create their own solutions without any limitations.
True or false: Power users can extend existing standard solutions by creating new computed satellites in their user space.
True or false: Power users can extend existing standard solutions by creating new computed satellites in their user space.
True or false: The primary issue faced by the business user mentioned in the text is that the data from web servers does not fit into the spreadsheet application anymore.
True or false: The primary issue faced by the business user mentioned in the text is that the data from web servers does not fit into the spreadsheet application anymore.
True or false: Managed Self-Service BI is a concept based on the Data Vault 2.0 architecture and extends it by user space.
True or false: Managed Self-Service BI is a concept based on the Data Vault 2.0 architecture and extends it by user space.
True or false: Industrialization monitoring helps identify solutions that exceed defined thresholds in terms of impact, stability, security violations, and resource consumption.
True or false: Industrialization monitoring helps identify solutions that exceed defined thresholds in terms of impact, stability, security violations, and resource consumption.
Match the following terms with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their descriptions in the context of Managed Self-Service BI:
Match the following statements with their correct value:
Match the following statements with their correct value:
Match the following terms with their correct usage in the context of Managed Self-Service BI:
Match the following terms with their correct usage in the context of Managed Self-Service BI:
Match the following concepts with their definitions in the context of Managed Self-Service BI:
Match the following concepts with their definitions in the context of Managed Self-Service BI:
Match the following terms with their correct descriptions in the context of Managed Self-Service BI:
Match the following terms with their correct descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following guidelines with their descriptions in the context of Managed Self-Service BI:
Match the following guidelines with their descriptions in the context of Managed Self-Service BI:
Match the following scenarios with their descriptions in the context of Managed Self-Service BI:
Match the following scenarios with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following user types with their level of expertise in BI dashboarding software:
Match the following user types with their level of expertise in BI dashboarding software:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of data analytics platform:
Match the following terms with their definitions in the context of data analytics platform:
Match the following user types with their level of expertise in the data analytics platform:
Match the following user types with their level of expertise in the data analytics platform:
Match the following key concepts with their descriptions in the context of Managed Self-Service BI:
Match the following key concepts with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following aspects with their management requirements in the context of Managed Self-Service BI:
Match the following aspects with their management requirements in the context of Managed Self-Service BI:
Match the following scenarios with their possible outcomes in managed self-service BI:
Match the following scenarios with their possible outcomes in managed self-service BI:
Match the following concepts with their impact on Managed Self-Service BI:
Match the following concepts with their impact on Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following statements with their correctness according to the text:
Match the following statements with their correctness according to the text:
Match the following terms with their corresponding roles in Managed Self-Service BI:
Match the following terms with their corresponding roles in Managed Self-Service BI:
Match the following entities with their roles in the Managed Self-Service BI environment:
Match the following entities with their roles in the Managed Self-Service BI environment:
Match the following concepts with their descriptions:
Match the following concepts with their descriptions:
Match the following statements with their correct answers:
Match the following statements with their correct answers:
Match the following concepts with their correct statements:
Match the following concepts with their correct statements:
Match the following concepts with their correct descriptions:
Match the following concepts with their correct descriptions:
Match the following statements with their correct concepts:
Match the following statements with their correct concepts:
Match the following terms with their correct descriptions in the context of Managed Self-Service BI:
Match the following terms with their correct descriptions in the context of Managed Self-Service BI:
Match the following best practices with their correct descriptions in the context of Managed Self-Service BI:
Match the following best practices with their correct descriptions in the context of Managed Self-Service BI:
Match the following concepts with their correct statements in the context of Managed Self-Service BI:
Match the following concepts with their correct statements in the context of Managed Self-Service BI:
Match the following scenarios with their possible outcomes in managed self-service BI:
Match the following scenarios with their possible outcomes in managed self-service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their descriptions in the context of Managed Self-Service BI:
Match the following statements with their correct concepts in the context of Managed Self-Service BI:
Match the following statements with their correct concepts in the context of Managed Self-Service BI:
Match the following scenarios with their descriptions in the context of Managed Self-Service BI:
Match the following scenarios with their descriptions in the context of Managed Self-Service BI:
Match the following aspects with their management requirements in the context of Managed Self-Service BI:
Match the following aspects with their management requirements in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following aspects with their management requirements in the context of Managed Self-Service BI:
Match the following aspects with their management requirements in the context of Managed Self-Service BI:
Match the following terms with their corresponding roles in Managed Self-Service BI:
Match the following terms with their corresponding roles in Managed Self-Service BI:
Match the following entities with their roles in the Managed Self-Service BI environment:
Match the following entities with their roles in the Managed Self-Service BI environment:
Match the following scenarios with their outcomes in the context of Managed Self-Service BI:
Match the following scenarios with their outcomes in the context of Managed Self-Service BI:
Match the following statements with their correctness in the context of Managed Self-Service BI:
Match the following statements with their correctness in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following entities with their roles in the Managed Self-Service BI environment:
Match the following entities with their roles in the Managed Self-Service BI environment:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following user types with their level of expertise in BI dashboarding software, according to the text:
Match the following user types with their level of expertise in BI dashboarding software, according to the text:
Match the following scenarios with the user types, according to the text:
Match the following scenarios with the user types, according to the text:
Match the following concepts with their correct statements, according to the text:
Match the following concepts with their correct statements, according to the text:
Match the following terms with their correct usage in the context of Managed Self-Service BI:
Match the following terms with their correct usage in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following terms with their correct usage in the context of Managed Self-Service BI:
Match the following terms with their correct usage in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following terms with their definitions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Match the following concepts with their descriptions in the context of Managed Self-Service BI:
Study Notes
Managed Self-Service BI with Data Vault 2.0
- The concept of managed self-service BI is used to transform organizations into data-driven organizations by making data and information widely available to decision-makers.
- The goal is to turn gut-feeling decisions into rational, informed decisions by educated decision-makers.
Reasons for Self-Service and Data Science
- Managed self-service BI supports two major use cases:
- Power users who want to extend the data analytics platform by additional, custom-built solutions.
- Data science use cases where the final solution is often not built on the data analytics platform or is only used for ad-hoc solutions.
Self-Service BI
- The common solution is to use technological solutions that allow power users and data scientists to access data sources directly, circumventing the centralized data warehouse, and build their own solutions.
- This approach can lead to inconsistencies, reinvention of business logic, and regulatory issues.
Managed Self-Service BI Architecture
- The architecture extends the Data Vault 2.0 architecture by adding a user space, which is not limited to the relational database.
- The user space is managed by power users who build their own solutions, and it is similar to sandboxing in other self-service approaches, but without a time limitation.
User Space
- The user space is a "green field" where power users can create their own solutions, following best practices such as Data Vault notation and dimensional modeling.
- The user space can be secured, and access can be controlled, with fences for data and information security, privacy, and auditability.
Managing Self-Service BI
- The issue with pure self-service BI is that it lacks management, and power users can do whatever they want, which can lead to a mess.
- The "managing" in managed self-service BI involves setting up guidelines, monitoring, and supporting power users, including data governance, infrastructure management, and support processes.
Industrialization
- Once a solution in the user space exceeds defined thresholds, it deserves additional review and industrialization, which involves analyzing the solution, redesigning it if necessary, and re-implementing it in the IT-controlled area of the data analytics platform.
Use Cases
- Examples of using managed self-service BI include:
- Prototyping new data-driven solutions, where business users can try out new ideas and generate revenue.
- Extending existing standard solutions by customizing them with additional dimensions and business rules.### Managed Self-Service BI
- Managed self-service BI is a pattern that combines the benefits of self-service BI with the security and privacy features of Data Vault 2.0.
- It empowers traditional organizations to become data-driven by making data widely available in a timely manner, within the limits set by the security team.
The Goal of Managed Self-Service BI
- The goal is to turn gut-feeling-based decisions into rational decisions made by educated, knowledgeable decision-makers.
- Every employee, from C-level executives to frontline workers, needs data to make decisions.
Reasons for Self-Service and Data Science
- Managed self-service BI supports two major use cases:
- Power users who want to extend the data analytics platform with custom-built solutions.
- Data scientists who want to augment data flows with additional raw data and business logic.
Issues with Self-Service BI
- Without management, self-service BI can lead to:
- Reinvention of the wheel (recreating business logic and transformation logic).
- Inconsistencies due to different interpretations of documentation.
- Regulatory issues (e.g., GDPR) when extracting data directly from source systems.
Managed Self-Service BI Architecture
- The architecture extends the Data Vault 2.0 architecture by adding a user space, where power users can build their own solutions.
- The user space is managed by power users, while the IT-controlled area above the user space is controlled by the data warehouse team.
Managing Self-Service BI
- Management involves:
- Fences (guidelines) for data and information security, privacy, and auditability.
- Monitoring the user space for adherence to guidelines and resource consumption.
- Industrialization of solutions that exceed defined thresholds.
Industrialization
- Identifying solutions that exceed thresholds (impact, stability, security, resource consumption).
- Analyzing, redesigning, and re-implementing solutions from the user space to the IT-controlled area.
- The goal is to make solutions more scalable, secure, and maintainable.### Customizing Standard Solutions
- A power user can extend existing standard solutions by creating a new computed satellite in the user space based on a satellite from the Raw Data Vault or Business Vault.
- The user-defined satellite only exists in the user space and can be used to create a custom dimension.
- The power user can copy the DDL statement for a dimension view in an information mart and customize it to use the satellite data from the user space.
Creating Custom Dimensions
- A power user cannot create anything in the IT-driven area of the architecture, so they must create custom dimensions in the user space.
- The custom dimension can be consumed by a custom-built dashboard, replacing the standard dimension with the modified dimension.
Distinguishing Between Reports
- It can be hard to distinguish between standard reports built by the data analytics team and power user reports.
- To help casual users distinguish between these reports, it is advised to add a footnote to standard reports indicating that they were built by the data analytics team.
- Power users can add any footnote they want, but should not claim that a report was built by the data analytics team.
Managed Self-Service BI
- Managed Self-Service BI is a pattern that works well with business-driven organizations.
- It allows for the adoption of the platform and the agility of the data analytics team to provide data to decision makers.
- Data Vault 2.0 helps organizations make data widely available in time, within limits set by the security team.
About the Author
- Michael Olschimke is the co-founder and CEO of Scalefree International GmbH, a Big-Data consulting firm in Europe.
- He has trained thousands of data warehousing individuals and publishes on related topics regularly.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Test your knowledge of user space advantages in data analytics platforms with this quiz. Learn about monitoring adherence to guidelines and retrieving grants for accessing solutions. Explore how these features can be applied to email servers and scanning for specific content.