4 - A team game Flashcards
What is the most important qualification for success in data transformation?
A willingness to do things differently.
What are the three key quotients mentioned for a successful data team?
- Practical quotient (PQ)
- Adaptability quotient (AQ)
- Retention quotient (RQ)
What does cognitive diversity refer to?
The inclusion of people with different perspectives and problem-solving approaches.
What is the standard recruitment process often criticized for?
Focusing on acquired skills.
Who was the first known Chief Data Officer (CDO)?
Cathryne Clay Doss, appointed in 2002 by Capital One.
What role does a CDO play in a company?
Leads the data team.
What is one skill that team members need according to the text?
The ability to link abstract ideas to real life.
True or False: Technical skills alone are sufficient for success in data transformation.
False.
What should be avoided in team recruitment for data transformation?
Focusing solely on technical skills like programming languages.
Fill in the blank: The ability to __________ is crucial for problem-solving in data transformation.
adapt
What does the term ‘Turingness’ refer to in the context of team attributes?
The ability to think creatively and apply abstract ideas to real-world problems.
What is the significance of teamwork under time pressure in data projects?
It enhances practical problem-solving skills.
What is a common issue with résumés in the recruitment process?
They are often optimized for algorithms rather than reflecting true problem-solving skills.
What experience did the author have that sparked an interest in problem-solving?
Participating in the Airmen Selection Test (AST) at age nine.
What does the author suggest is often the real constraint to success in data projects?
A lack of willingness to rethink and innovate.
What is the ‘résumé problem’ in recruitment?
Résumés focus on learned skills rather than problem-solving abilities.
What did the author learn from rowing at an international level?
The value of teamwork and discipline in problem-solving.
What can a successful data team member be compared to in terms of skills?
- Chemist
- Entrepreneur
- Engineer
According to the text, what is often the outcome of ‘code-first’ thinking in data projects?
Lack of progress due to unclear problem definitions.
What is the impact of previous failed attempts at data projects on new initiatives?
They create a scarring effect, leading to distrust in new teams.
What is a key attribute that the author looks for in team members?
The ability to share and communicate effectively.
What is a potential downside of quick solutions in problem-solving?
They might add another layer of dysfunction that complicates future problem-solving.
Quick fixes can lead to recurring issues in organizational problems.
What skill set should recruiters prioritize when building a team?
Business focus, ability to share and discuss problems, holistic decision-making.
Wider skill sets are preferred over a narrow ‘code-first’ mentality.
What does RQ stand for in the context of recruiting?
Retention Quotient.
RQ refers to the ability to store and recall information easily.
Why are traditional intelligence measures like IQ and RQ not sufficient in recruiting?
They do not encompass emotional intelligence (EQ), practical quotient (PQ), and adaptability quotient (AQ).
A balance of these quotients is necessary for effective team dynamics.
Define Practical Quotient (PQ).
The ability to think about problem-solving in a business-related manner and solve data problems effectively.
High PQ relates to conceptualizing and delivering solutions.
What is Adaptability Quotient (AQ)?
The ability to adapt thinking across different domains, such as programming in multiple languages.
High AQ indicates flexibility in problem-solving.
What is the ‘heaven and hell problem’?
A scenario where one must choose between two doors, one leading to a solution and the other to failure, with one person lying and one telling the truth.
This problem tests critical thinking and problem breakdown skills.
What is a good way to describe a car from a data perspective?
Different types, classification by make and model, functionality, and the information provided by its dashboard.
This approach emphasizes understanding data definitions and user needs.
What should you be cautious of when presented with pre-selected team members from HR?
Question why they are available and avoid inheriting overly specialized skills.
Specialists may not fit the broader needs of your team.
What is cognitive diversity?
Differences in how people prefer to think, focusing on problem-solving styles rather than background diversity.
It includes various thinking preferences such as analytical, practical, relational, and experimental.
Name the four modes of thinking according to the Herrmann model.
- Analytical
- Practical
- Relational
- Experimental
Each mode represents different problem-solving approaches.
What is a key reason data teams fail to deliver value?
Lack of alignment of roles to create business value and unclear purpose of roles.
Proper structure and clarity are essential for success.
What should be ensured when creating a data and analytics team?
All capabilities are represented in the overall structure and no capability gaps exist.
This ensures comprehensive problem-solving and effectiveness.
What does data product management involve?
Ownership of data products and ensuring their alignment with business needs.
This role is crucial for successful data implementation.
True or False: Cognitive diversity can help prevent a team from agreeing on a single answer to every problem.
True.
Diverse thinking promotes varied solutions and creativity.
What is the main purpose of having a clear data process?
To enable teams to know how they work together.
What are the key activities of Data Product Management?
- Business problems are clearly expressed and understood by the business.
- Detailed requirements are written and signed off by the business.
- Pipeline of all work is managed and prioritized.
- Roadmap for each product is managed and aligned to the overall business strategy.
- Data roadmaps are communicated to customers, suppliers, execs, business sponsors, data stewards, and practitioners.
Who does the Data Product Management team interact with?
- Data science
- Data engineering
- Data operations
- Data architecture
What is the role of the Data Science team?
To develop and continuously improve models, AI, and ML capabilities that deliver value to the business.
What are the key activities of the Data Science team?
- Best practice data science capabilities are developed.
- The ‘art of the possible’ use of DS is understood and explained.
- Data models, statistical models, and algorithms are developed.
- Models and algorithms are kept up to date.
- Latest data sets from data engineering are used.
- Business recommendations are made based on data models.
What are the key activities of the Data Engineering team?
- Product roadmaps are followed for capturing data sources and integrating with the data model and data infrastructure.
- Data quality and data roadmaps are used across the organization.
- Quality and governance of all data are managed to a high standard.
- Data products such as warehouse, data lake, or APIs are developed.
- APIs and data feeds are built.
- Dashboards and reports are developed in line with product roadmaps.
What is the focus of Data Security and Privacy?
To ensure that the company’s data assets are protected, secure, and used ethically.
What are the key activities related to Data Security and Privacy?
- Data privacy and data security policies are written and maintained.
- Data is properly classified and used in line with company privacy and data security policies.
- GDPR and other data regulations are understood and implemented.
- Privacy and security are designed into all data products.
What is the role of Data Operations?
To ensure that data products are deployed, accessible, and properly supported across the business, customers, and suppliers.
What are the key activities of Data Operations?
- Data products are accessible by the intended audience during agreed operating hours.
- The environment for operating data products is stable and performant.
- Data products are supported in line with SLAs.
What are the key activities of the Data Architecture team?
- All data activities have the right environment to capture, store, transmit, manage, and access data efficiently.
- All data tools support an integrated, end-to-end data process.
- The data model is designed and used as the single view of data across the organization.
- Data across platforms and applications is integrated using APIs and data feeds.
What is the role of Data Oversight?
To ensure independent oversight of data capabilities and operations.
What are the key activities of Data Oversight?
- The work by data teams is independently scrutinized for alignment to business goals and objectives.
- Data teams are supported and roadblocks removed.
What is the focus of the Data Community?
To ensure data is at the heart of everything and that the work of data teams is given relevant and specific feedback.
What are the key activities of the Data Community?
- Specific and relevant input to products, product roadmap, and projects.
- Data teams’ output is tested.
What are the limiting factors for the success of a data team?
- Lack of alignment of roles to creating business value.
- Clarity and purpose of roles.
- Ensuring nothing falls through the cracks between different roles.
True or False: Coding skills are more important than problem-solving ability in leading a data team.
False
Fill in the blank: When recruiting, cast a _______.
[wide net]
What is vital to the success of a data team job?
Interaction with the entire business, not just those who understand data.
