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Survey on Building a Competent Data Science Team 

Big Data analytics can turn cutting-edge technology into actionable insights, Nowadays, more and more organizations are opening up their doors to big data and using data science to power business value —increasing the value of a data scientist who knows how to tease actionable insights out of gigabytes of data.

To achieve that, what skills or qualities that an ideal data scientist should possess? 

This survey aims to take a closer look at that list of essential skills and understand more the technical and competence skills a corporate data science team is supposed to have.

Thank you for taking part in this important survey.
This survey should only take 4-5 minutes to complete.  Be assured that all answers you provide will be kept in the strictest confidentiality.  Survey results will be summarized and sent to all those who fully complete the survey.

Also, respondents may be invited to join our networking session later on to learn how to multiply the value of their data assets by adopting the right data analytics solutions.

Should you have any enquiry on this survey, please contact ceo@secgadata.com

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Privacy Disclaimer:
Thanks for taking this survey. By joining the survey, you agree that the information you supply may be used to inform you of related products or services from the Organizer or its business partners.

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This questionnaire is divided into the below sections.  In each section, there is around 3-4 questions.

1.    Software/System/Product Test Planning Technical Skills
2.    Stakeholder Management Technical Skills
3.    Solution Architecture Technical Skills
4.    Programme Management Competence Skills
5.    Emerging Technology Synthesis Technical Skills
6.    Data Visualization Technical Skills
7.    Data Strategy Competency Skills
8.    Data Governance Competence Skills
9.    Data Design Competence Skills
10.  Business Needs Analysis Competence Skills
11.  Analytics and Computational Modelling Technical Skills
12.  Business Innovation Competence Skills
13.  Organizational Data Science Team
1.Please fill in your contact information.  
Registrants who have successfully registered for the luncheon will get a notification email by Dec 6, 2019.(Required.)
Why Data Science Matters
2.The Data Science Team can develop a test strategy and establish testing policies, guidelines and metrics according to both internal and external standards
Stakeholder Management Technical Skills
3.The Data Science Team can identify key stakeholder relationships, needs and interests, and coordinate with stakeholders on regular basis
4.The Data Science Team can serve as the organization's main contact point for stakeholder communication and engaging them to align interest
5.The Data Science Team can develop a stakeholder engagement plan and negotiate with stakeholders to arrive at mutually beneficial agreement
6.The Data Science Team can define a strategic stakeholder management roadmap and lead critical discussions and negotiations
7.The Data Science Team can establish the overall vision for the alignment of objectives among organizations and stakeholders, co-creating shared goals and strategic initiatives with senior stakeholders
Solution Architecture Technical Skills
8.The Data Science Team can develop a solution architecture and prepare a technical blueprint for a given area, demonstrating how the solution address requirements
9.The Data Science Team can establish frameworks and determine relevant tools and techniques to guide the development of IT solutions
10.The Data Science Team can synthesis new trends and developments in or beyond ICT, and lead the development of innovative and impactful industry ground breaking solutions
Programme Management Competence Skills
11.The Data Science Team can oversee small projects or programmes, managing timeline, resources, risks and stakeholders
12.The Data Science Team can plan and drive medium scale projects or programmes, including allocating resources to different parts, and engaging stakeholders on the project's progress and outcomes
13.The Data Science Team can lead end-to-end management of large programmes or multiple projects concurrently, coordinating projects inter-dependencies
14.The Data Science Team can direct the management and authorize ownership of multiple large, complex programmes and projects, ensuring alignment with strategic business priorities
Emerging Technology Synthesis Technical Skills
15.The Data Science Team can conduct research and identify opportunities for new and emerging technology to support the business
16.The Data Science Team can evaluate new and emerging technology and trends against the organizational needs and process
17.The Data Science Team can establish internal structures and processes to guide the exploration, integration and evaluation of new technologies
18.The Data Science Team can establish an emerging technology strategy and sprearhead organizational norms to synthesis and leverage new technologies and trends to propel business growth
Data Visualization Technical Skills
19.The Data Science Team can select appropriate visualization techniques and develop dashboards to reflect data trends and findings
20.The Data Science Team can design data displays to present trends and finding, incorporating new and advanced visualization techniques and analytics capabilities
21.The Data Science Team can establish an effective data visualization architecture and design intelligent and adaptable displays employing optimal delivery modes, mechanisms and timings
Data Strategy Competency Skills
22.The Data Science Team can develop data management structures and recommend policies, processes and tools for effective data storage, handling and ulitisation
23.The Data Science Team can establish data management strategies to extract maximum value from information assets and support decision-making and business processess
24.The Data Science Team can define a coherent data strategy and sprearhead new approaches to enrich, synthesis and apply data, to maximize the value of data as a critical business asset and driver
Data Governance Competence Skills
25.The Data Science Team can implement guidelines, laws, statutes and regulations on appropriate handling of data at various stages in their lifecycle, and monitor compliance with data policies
26.The Data Science Team can develop organization practices and standards for handling data throughout their lifecycle, resolve breaches, and oversee transfer of data between organizations
27.The Data Science Team can establish policies for data security and usage, facilitate industry consensus around data ethics, and provide expert advice on data transfer across geographies
Data Design Competence Skills
28.The Data Science Team can identify data requirements and support the design of database models, incorporating parameters, fields and mechanisms for the maintenance, storage and retrieval of data
29.The Data Science Team can design data models and data flow diagrams and mechanisms to optimize the flow, maintenance, storage and retrieval of data
30.The Data Science Team can establish a strategy for the creation of large-scale data models and structures and sprearhead the implementation of database technology, architectures, software and facilities
Business Needs Analysis Competence Skills
31.The Data Science Team can document business requirements and identify basic needs as wells as potential solutions
32.The Data Science Team can elicit and analyse business requirements from key stakeholders and assess relevant solutions and their potential impact
33.The Data Science Team can investigate existing business process, evaluate requirement and define the scope for recommended solutions and porgrammes
34.The Data Science Team can lead comprehensive analysis to understand underlying drivers and present a compelling business case for proposed solutions
Analytics and Computational Modelling Technical Skills
35.The Data Science Team can perform basic data analysis in conducting basic statistical modelling, drawing accurate inference from the data
36.The Data Science Team can identify and utilize appropriate statistical algorithms and data models to test hypothesis and derive patterns or solutions
37.The Data Science Team can develop and utilize new algorithms and advanced statistical models to enable the production of desired outcomes
38.The Data Science Team can design advanced statistical and computational models, and spearhead the application of algorithms and modelling techniques to new domains
Business Innovation Competence Skills
39.The Data Science Team can explore opportunities for business innovation and reform, and lead the implementation of innovative business initiatives
40.The Data Science Team can prioritize business innovation opportunities and design digital architectures and processes to facilitate the creation of an innovative business environment
41.The Data Science Team can inspire a culture of business and digital innovation within and beyond the organization
Organizational Data Science Team
42.The Organization's Data Scientist can manage projects, prepare datasets, analyse data and present insights
43.The Organization's Senior Data Scientist can implement data strategy, manage projects, analyse data and present insights
44.The Organization's Chief Data Scientist can set data strategy, identify business needs, oversee data analytics, translate insights into results and manage departments