Auradata
Why This Board Exists
Strategic Platform Assessment
Select a category to explore the questions. Click any question to see the detailed Scikiq answer.
A. Strategic & Business Alignment
- What are the top 3 business objectives this data platform must support?
- What is our current Data Maturity Level and what level do we need to reach?
- What is the expected Return on Investment (ROI) and how will we measure it?
- Who are the primary end-users and what are their specific needs?
- What existing pain points are we trying to eliminate?
- How will this platform help us achieve a "single source of truth"?
- Does the platform support industry-specific use cases?
- How quickly can we expect to move from deployment to actionable insights?
- Will this platform help democratize data access across the organization?
- Does the platform support the shift to a "data product" operating model?
B. Data Integration & Connectivity
- What types of data sources can the platform connect to natively?
- Does it support batch, streaming (real-time), and change data capture (CDC)?
- Can the platform handle structured, semi-structured, and unstructured data?
- How does the platform facilitate data transformation (ETL/ELT)?
- What is the process for adding a brand new data source?
- How does the platform handle data lineage to track data movement?
- Does the platform offer a unified view regardless of where data resides?
- Can the platform connect to and work across multi-cloud/hybrid-cloud environments?
- How does the platform ensure consistency and interoperability?
- Does it provide an API-first architecture for integration?
C. Data Quality, Governance & Security
- What specific features ensure data quality?
- How is Identity Resolution performed to create a unified view?
- Does the platform offer a central Data Catalog?
- How does the platform help us comply with regulations (GDPR, CCPA)?
- Can we implement role-based access control (RBAC)?
- What are the platform's data encryption capabilities?
- Does the platform support automated data masking and anonymization?
- How are audit logs and access history maintained?
- Does the platform provide tools for Master Data Management (MDM)?
- What is the platform's approach to data governance policy automation?
D. Analytics, AI & Machine Learning
- Does the platform support real-time analytics and querying?
- What Business Intelligence (BI) tools does the platform integrate with?
- Does the platform include a built-in visualization tool?
- Is there native support for Machine Learning (ML) and AI frameworks?
- How does the platform enable predictive and prescriptive analytics?
- Does the platform offer Natural Language Query (NLQ) capabilities?
- Can data science teams easily access and prep governed data within the platform?
- What features are available for hyper-personalization?
- Does the platform facilitate the creation of an AI-Ready Semantics & Ontology?
- How does the platform help in automating data pipelines?
E. Technology, Pricing & Support
- Is the platform built on a modern, cloud-native architecture?
- How does the platform ensure scalability and elasticity?
- What is the pricing model? Is it transparent?
- What level of technical expertise is required?
- What is the quality and availability of technical support?
- What kind of documentation and training resources are provided?
- Does the platform offer a low-code/no-code interface?
- How frequently are platform updates and new features rolled out?
- What are the platform's security and uptime SLAs?
- What is the platform's lock-in risk?