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Question	Answer
In Data Steward, what is the maximum proficiency that one should possess in Domain Knowledge? Expert Entry Intermediate	Expert
In Data Steward, what is the maximum proficiency that one should possess in Data Governance? Expert Entry Intermediate	Expert
In Data Steward, what is the maximum proficiency that one should possess in Operational Analytics? Expert Entry Intermediate	Expert
In Data Steward, what is the maximum proficiency that one should possess in Data Visualization? Expert Entry Intermediate	Intermediate
In Data Steward, what is the maximum proficiency that one should possess in Research Methods? Expert Entry Intermediate	Entry
In Data Steward, what is the maximum proficiency that one should possess in Computing? Expert Entry Intermediate	Entry
In Data Engineer, what is the maximum proficiency that one should possess in Data Knowledge? Expert Entry Intermediate	Entry
In Data Engineer, what is the maximum proficiency that one should possess in Data Governance? Expert Entry Intermediate	Intermediate
In Data Engineer, what is the maximum proficiency that one should possess in Operational Analytics? Expert Entry Intermediate	Expert
In Data Engineer, what is the maximum proficiency that one should possess in Data Visualization? Expert Entry Intermediate	Entry
In Data Engineer, what is the maximum proficiency that one should possess in Research Methods? Expert Entry Intermediate	Entry
In Data Engineer, what is the maximum proficiency that one should possess in Data Engineering? Expert Entry Intermediate	Expert
In Data Engineer, what is the maximum proficiency that one should possess in Statistical Techniques? Expert Entry Intermediate	Entry
In Data Engineer, what is the maximum proficiency that one should possess in Methods and Algorithms? Expert Entry Intermediate	Entry
In Data Engineer, what is the maximum proficiency that one should possess in Computing? Expert Entry Intermediate	Entry
In Data Scientist, what is the maximum proficiency that one should possess in Domain Knowledge? Expert Entry Intermediate	Intermediate
In Data Scientist, what is the maximum proficiency that one should possess in Data Governance? Expert Entry Intermediate	Intermediate
In Data Scientist, what is the maximum proficiency that one should possess in Operational Analytics? Expert Entry Intermediate	Expert
In Data Scientist, what is the maximum proficiency that one should possess in Data Visualization? Expert Entry Intermediate	Intermediate
In Data Scientist, what is the maximum proficiency that one should possess in Research Methods? Expert Entry Intermediate	Intermediate
In Data Scientist, what is the maximum proficiency that one should possess in Data Engineering? Expert Entry Intermediate	Expert
In Data Scientist, what is the maximum proficiency that one should possess in Statistical Techniques? Expert Entry Intermediate	Expert
In Data Scientist, what is the maximum proficiency that one should possess in Methods and Algorithms? Expert Entry Intermediate	Expert
In Data Scientist, what is the maximum proficiency that one should possess in Computing? Expert Entry Intermediate	Expert
In Functional Analyst, what is the maximum proficiency that one should possess in Domain Knowledge? Expert Entry Intermediate	Expert
In Functional Analyst, what is the maximum proficiency that one should possess in Data Governance? Expert Entry Intermediate	Intermediate
In Functional Analyst, what is the maximum proficiency that one should possess in Operational Analytics? Expert Entry Intermediate	Expert
In Functional Analyst, what is the maximum proficiency that one should possess in Data Visualization? Expert Entry Intermediate	Expert
In Functional Analyst, what is the maximum proficiency that one should possess in Research Methods? Expert Entry Intermediate	Entry
In Functional Analyst, what is the maximum proficiency that one should possess in Computing? Expert Entry Intermediate	Entry
In Analytics Manager, what is the maximum proficiency that one should possess in Domain Knowledge? Expert Entry Intermediate	Expert
In Analytics Manager, what is the maximum proficiency that one should possess in Data Governance? Expert Entry Intermediate	Expert
In Analytics Manager, what is the maximum proficiency that one should possess in Operational Analytics? Expert Entry Intermediate	Expert
In Analytics Manager, what is the maximum proficiency that one should possess in Data Visualization? Expert Entry Intermediate	Expert
In Analytics Manager, what is the maximum proficiency that one should possess in Research Methods? Expert Entry Intermediate	Entry
In Analytics Manager, what is the maximum proficiency that one should possess in Data Engineering? Expert Entry Intermediate	Entry
In Analytics Manager, what is the maximum proficiency that one should possess in Statistical Techniques? Expert Entry Intermediate	Entry
In Analytics Manager, what is the maximum proficiency that one should possess in Methods and Algorithms? Expert Entry Intermediate	Entry
In Analytics Manager, what is the maximum proficiency that one should possess in Computing? Expert Entry Intermediate	Entry
This framework centers on Data Quality, Accessibility, and Security.	Data
Inconsistent, low-quality, and unstandardized data hinder meaningful analysis, compounded by a lack of strongly data-oriented groups.	Data - Level 1
Data is primarily standardized and structured within functional or process silos. However, there are limited discussion of data management among senior executives.	Data - Level 2
Key data domains have been identified, and central data repositories have been established.	Data - Level 3
Central repositories contains integrated, accurate, and commonly shared data. However, data remains predominantly an IT concern, with limited attention to unique data needs.	Data - Level 4
Continuous pursuit of new data and metrics, harnessing both structured and unstructured data such as text and video. Considers data as a strategic asset.	Data - Level 5
This framework is centered around the effective management of analytics resources, emphasizing seamless coordination and collaboration across the entirety of the enterprise.	Enterprise
Absence of an enterprise-wide perspective on data or analytics is evident, compounded by the challenge of poorly integrated systems	Enterprise - Level 1
The existence of islands of data, technology, and expertise signifies localized value delivery within specific areas or departments	Enterprise - Level 2
Emphasis on analytics is primarily centered around specific processes or business units, showcasing a focused approach.	Enterprise - Level 3
Key data, technology, and analytics professionals are strategically managed from an enterprise-wide perspective.	Enterprise - Level 4
Strategic focus is directed towards aligning key analytical resources with enterprise priorities and fostering differentiation	Enterprise - Level 5
This framework is anchored in robust and committed leadership that possesses a profound understanding of the significance of analytics. Their unwavering commitment is evident through consistent advocacy for the integration of analytics in decision-making	Leadership
Minimal awareness of or interest in analytics within the organization.	Leadership - Level 1
Local leaders are emerging, but there is a limited level of connectivity or collaboration among them.	Leadership - Level 2
Senior leaders demonstrate a recognition of the crucial importance of analytics and are actively committed to developing analytical capabilities within the organization.	Leadership - Level 3
Senior leaders are proactively involved in formulating analytical plans and actively contributing to the development of robust analytical capabilities within the organization.	Leadership - Level 4
Effective leaders exhibit analytical behavior and demonstrate a passionate commitment to fostering a culture of analytical competition within the organization.	Leadership - Level 5
This framework is crafted with a central focus on the strategic identification and selection of pivotal organizational targets. These carefully chosen targets serve as the cornerstone, laying the foundation for a comprehensive analytics roadmap.	Targets
The current landscape presents a challenge as there are no discernible opportunities for targeted initiatives or strategic interventions.	Targets - Level 1
The existing scenario features multiple disconnected targets that often lack strategic significance within the organizational context	Targets - Level 2
Analytical efforts are converging around a concise set of critical targets, showcasing a strategic alignment that emphasizes the prioritization of key objectives.	Targets - Level 3
Analytics initiatives are concentrated on a select few key business domains, with a clear focus on achieving explicit and ambitious outcomes	Targets - Level 4
Analytics has become an integral component of the company's distinctive capability and overarching strategy	Targets - Level 5
This framework is designed with a central focus on cultivating and fostering a cadre of high-performing analytics professionals. It prioritizes th	Analytics Professional
Limited number of skills are currently associated with specific functions within the organization.	Analytics Professional - Level 1
Isolated pockets of analytics professionals throughout the organization, and there is a lack of coordinated management regarding the mix of skills within these dispersed groups.	Analytics Professional - Level 2
Analytics professionals are acknowledged as key talent within the organization, with a strategic emphasis on directing their expertise towards pivotal business areas	Analytics Professional - Level 3
The organization actively recruits, develops, deploys, and engages highly capable analytics professionals.	Analytics Professional - Level 4
The organization boasts a cadre of world-class professional analytics experts. In addition, there is cultivation of analytical skills among amateurs across the entire enterprise, fostering a culture of analytical proficiency at all levels.	Analytics Professional - Level 5
This framework is built around the strategic integration of technologies to bolster analytics capabilities across the organization, ensuring a cohesive and efficient use of advanced tools for informed decision-making.	+Technology
The current state involves desktop technology and standard office packages being utilized, but there is a notable challenge in terms of poorly integrated systems.	+Technology - Level 1
Analytical efforts are conducted through individual initiatives, leveraging statistical packages, descriptive analytics, database querying, and tabulations.	+Technology - Level 2
The organization employs an enterprise-wide analytical plan, incorporating dedicated tools and platforms.	+Technology - Level 3
The organization employs an enterprise-wide analytical plan and processes, leveraging the capabilities of cloud-based big data solutions.	+Technology - Level 4
The organization boasts a sophisticated, enterprise-wide big data and analytics infrastructure, incorporating cognitive technologies	+Technology - Level 5
This framework revolves around the incorporation of a diverse range of analytical techniques, spanning from fundamental descriptive statistics to advanced machine learning methodologies.	+Analytical Techniques
The current analytical approach is predominantly ad-hoc, relying on simple mathematical methods, extrapolation, and trending for deriving insights.	Analytical Techniques - Level 1
Analytical methods encompass basic statistics, segmentations, database querying, and tabulations of key metrics, effectively harnessed to derive valuable insights.	Analytical Techniques - Level 2
The analytical approach involves employing simple predictive analytics, including techniques such as classification and clustering, to generate dynamic forecasts and enhance decision-making processes.	Analytical Techniques - Level 3
Utilizing advanced predictive methods, the organization deploys sophisticated techniques for uncovering insights.	Analytical Techniques - Level 4
The organization leverages cutting-edge technologies, including neural networks and deep learning, as well as advanced techniques such as genetic algorithms and machine learning, to push the boundaries of analytical capabilities	Analytical Techniques - Level 5
The organization faces challenges in conducting serious analytical work due to the absence of one or several prerequisites, including insufficient data, a shortage of analytical skills, or limited interest from senior management.	Analytically Impaired
While there are pockets of analytical activity within the organization, there is a lack of coordination and strategic focus. These disparate efforts may not align with	Localized Analytics
The organization aspires towards a more analytical future and has successfully established analytical capabilities with several significant initiatives currently underway. However, the pace of progress is hindered by challenges, often stemming fro	Analytical Aspirations
While the organization possesses the requisite human and technological resources and consistently applies analytics throughout its operations, there is a notable absence of a strategic focus grounded in analytics. Consequently, des	Analytical Companies
The organization has elevated analytics to a distinctive business capability, regularly leveraging it as a core strength. Adopting an enterprise-wide approach, the organization benefits from committed and involved	Analytical Competitors
5 Stages of Analytics Maturity	Analytically Impaired Localized Analytics Analytical Aspirations Analytical Companies Analytical Competitors
The following are the 5 stages of Analytics Maturity except for: Analytical Aspirations Analytical Competitors Analytical Data Localized Analytics Analytical Companies Analytically Impaired	Analytical Data
Which of the following stages that has all the analytical resources but lacks focus? Localized Analytics Analytical Competitors Analytically Impaired Analytical Companies Analytical Data Analytical Aspirations	Analytical Companies
The following are the authors of the book 'Competing on Analytics: The New Science of Winning' except for: Thomas Davenport Robert Morison Jeanne Harris	Robert Morison
Which of the following stages that has all the analytical resources and regularly leveraging it as their strength? Analytical Companies Analytical Aspirations Analytical Competitors Analytical Data Analytically Impaired Localized Analytics	Analytical Competitors
In DELTA+ Model, which of the following components encompasses strategic integration. Targets Data Analytical Techniques Technology Enterprise Leadership	Technology
In DELTA+ Model, which of the following components encompasses effective management? Data Targets Leadership Analytical Professional Enterprise Technology	Enterpriset
Which of the following stages that has analytical activity but lacks coordination? Analytical Data Localized Analytics Analytical Aspirations Analytical Companies Analytical Competitors Analytically Impaired	Localized Analytics
In DELTA+ Model, which of the following components encompasses strategic identification and selection? Analytical Professional Leadership Targets Enterprise Data Technology	Targets
In DELTA+ Model, which of the following components encompasses cultivation of professionals. Data Leadership Enterprise Technology Analytical Professional Targets	Analytical Professional
In DELTA+ Model, which of the following components encompasses Data Quality, Accessibility and Security? Enterprise Technology Data Analytical Professionals Leadership Targets	Data
Which of the following faces challenges in conducting analytical work? Analytical Competitors Localized Analytics Analytical Aspirations Analytical Companies Analytical Data Analytically Impaired	Analytically Impaired
In DELTA+ Model, which of the following components encompasses profound understanding of analytics?	Leadership
Which of the following stages that has analytical future?	Analytical Aspirations
The following are the authors of the book 'Analytics at Work: Smarter Decisions, Better Results' except for: Jeanne Harris Robert Morison Jim Harris Thomas Davenport	Jim Harris
What organization introduces the Professional Maturity Model?	AAP

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