Data Strategy Assessment
Data Strategy Assessment (DSA) with DIVNT
Data Strategy Assessment (DSA) with DIVNT
Data Strategy Assessment (DSA) with DIVNT
Maturity Assessment
Maturity Assessment
Enable the database for AI capabilities
Enable the database for AI capabilities
Breaking down data silos
Breaking down data silos
These companies trust DIVINT
These companies trust DIVINT
These companies trust DIVINT
Our DSA Focus Areas at a Glance
Our DSA Focus Areas at a Glance
Analysis & Discovery (Current State Assessment)
Independent assessment of your data landscape: systems, interfaces, data sources, BI/controlling, risks, and obstacles. A clear overview instead of fragmented views.
Analysis & Discovery (Current State Assessment)
Independent assessment of your data landscape: systems, interfaces, data sources, BI/controlling, risks, and obstacles. A clear overview instead of fragmented views.
Analysis & Discovery (Current State Assessment)
Independent assessment of your data landscape: systems, interfaces, data sources, BI/controlling, risks, and obstacles. A clear overview instead of fragmented views.
Goals, Vision & Use Case Prioritization
Develop shared visions, identify concrete use cases, and prioritize them based on business impact and feasibility – including success criteria (KPIs).
Goals, Vision & Use Case Prioritization
Develop shared visions, identify concrete use cases, and prioritize them based on business impact and feasibility – including success criteria (KPIs).
Goals, Vision & Use Case Prioritization
Develop shared visions, identify concrete use cases, and prioritize them based on business impact and feasibility – including success criteria (KPIs).
Target Architecture & Migration Roadmap
Design the technical target architecture (DWH/Lakehouse, Integration, Governance) and plan a pragmatic, risk-minimized path to achieve it – including steps, milestones, and responsibilities.
Target Architecture & Migration Roadmap
Design the technical target architecture (DWH/Lakehouse, Integration, Governance) and plan a pragmatic, risk-minimized path to achieve it – including steps, milestones, and responsibilities.
Target Architecture & Migration Roadmap
Design the technical target architecture (DWH/Lakehouse, Integration, Governance) and plan a pragmatic, risk-minimized path to achieve it – including steps, milestones, and responsibilities.
Data Governance & Operating Model
Define roles, processes, and policies (Ownership, Data Stewardship, Quality, Security). Auditable standards for access, data protection, and lifecycle.
Data Governance & Operating Model
Define roles, processes, and policies (Ownership, Data Stewardship, Quality, Security). Auditable standards for access, data protection, and lifecycle.
Data Governance & Operating Model
Define roles, processes, and policies (Ownership, Data Stewardship, Quality, Security). Auditable standards for access, data protection, and lifecycle.
Data Integration, Automation & Quality
ETL/ELT strategy, real-time/batch processing, data catalogs, quality rules, and automation for robust, reusable data products.
Data Integration, Automation & Quality
ETL/ELT strategy, real-time/batch processing, data catalogs, quality rules, and automation for robust, reusable data products.
Data Integration, Automation & Quality
ETL/ELT strategy, real-time/batch processing, data catalogs, quality rules, and automation for robust, reusable data products.
Analytics, Self-Service & Empowerment
Foundation for BI/AI: curated datasets, KPI catalogs, self-service guidelines, training sessions. This makes data analytics usable in everyday life.
Analytics, Self-Service & Empowerment
Foundation for BI/AI: curated datasets, KPI catalogs, self-service guidelines, training sessions. This makes data analytics usable in everyday life.
Analytics, Self-Service & Empowerment
Foundation for BI/AI: curated datasets, KPI catalogs, self-service guidelines, training sessions. This makes data analytics usable in everyday life.
Why a Data Strategy Assessment – and What Happens Without One?
With DIVINT as your partner, you benefit from clear added value. Without a data strategy assessment, valuable potentials remain untapped:
With DIVINT DSA
With DIVINT DSA
Benefits
Clear overview of systems, data flows, and responsibilities
Prioritized use cases with a business case instead of technology for technology's sake
Target architecture & roadmap for rapid, measurable progress
Automation reduces manual data search/preparation, resulting in up to approximately 30% time savings
Early identified risks & limits (Security, Quality, Scalability)
Solid foundation for BI/AI, monetization, and data-driven decisions
Without DSA
Disadvantages
Opaque data landscape, redundancy, and shadow reporting
Costly misinvestments in tools without a viable strategy
Slow decisions due to manual data collection
Security/compliance gaps and unclear responsibilities
Island solutions instead of scalable data architecture
Missed use case potentials and ROI opportunities
Frequently Asked Questions
What does a data strategy assessment include?
An independent analysis of architecture, processes, and data quality, leading to a vision, target architecture, prioritized use cases, roadmap, cost/effort estimates, and specific recommendations.
What does a data strategy assessment include?
An independent analysis of architecture, processes, and data quality, leading to a vision, target architecture, prioritized use cases, roadmap, cost/effort estimates, and specific recommendations.
Who is suitable for a DSA?
For decision-makers and key users (service, sales, production, quality assurance, etc.), data leaders, data engineers, and business users—up to 12 people can actively participate in workshops.
Who is suitable for a DSA?
For decision-makers and key users (service, sales, production, quality assurance, etc.), data leaders, data engineers, and business users—up to 12 people can actively participate in workshops.
How does a typical DSA session proceed?
In three phases: Analysis & Discovery, Goals/Vision & Use-Case Prioritization, Presentation of Results with Roadmap & Recommendations. Format: compact workshops (e.g., each lasting 4 hours) plus development phase.
How does a typical DSA session proceed?
In three phases: Analysis & Discovery, Goals/Vision & Use-Case Prioritization, Presentation of Results with Roadmap & Recommendations. Format: compact workshops (e.g., each lasting 4 hours) plus development phase.
How long does a DSA take?
Depending on the depth, the process can take 3 days (workshop + results presentation) up to 4 working days in 5 steps; more comprehensive versions take 6–8 weeks (4 phases) with in-depth analysis and target architecture.
How long does a DSA take?
Depending on the depth, the process can take 3 days (workshop + results presentation) up to 4 working days in 5 steps; more comprehensive versions take 6–8 weeks (4 phases) with in-depth analysis and target architecture.
Are the workshops also available remotely?
Yes. Completely virtual or hybrid – with secure access for demos and review sessions.
Are the workshops also available remotely?
Yes. Completely virtual or hybrid – with secure access for demos and review sessions.
Which technologies are being considered?
Vendor-neutral: modern data platforms (DWH/Lakehouse, Data Lakes), data virtualization, and cloud components. Commonly used: Microsoft Azure/Power BI/Fabric, alongside others like Databricks, Denodo, Qlik, Snowflake, AWS, SAP, Oracle.
Which technologies are being considered?
Vendor-neutral: modern data platforms (DWH/Lakehouse, Data Lakes), data virtualization, and cloud components. Commonly used: Microsoft Azure/Power BI/Fabric, alongside others like Databricks, Denodo, Qlik, Snowflake, AWS, SAP, Oracle.
What results can I expect?
Independent assessment of the IT/data landscape, shared vision, prioritized use cases, technical target architecture, roadmap, cost/effort indication, and concrete action recommendations – foundations for data-driven decisions and monetization.
What results can I expect?
Independent assessment of the IT/data landscape, shared vision, prioritized use cases, technical target architecture, roadmap, cost/effort indication, and concrete action recommendations – foundations for data-driven decisions and monetization.
What next steps do you recommend?
Initial non-binding consultation, scoping of the DSA (objectives, participants, available materials), scheduling of workshops, data review – followed by the start of the analysis phase and scheduling of the results presentation.
What next steps do you recommend?
Initial non-binding consultation, scoping of the DSA (objectives, participants, available materials), scheduling of workshops, data review – followed by the start of the analysis phase and scheduling of the results presentation.
Thang Nguyen
CEO, DIVINT
In a complimentary consultation, discover how Fabric can transform your business
Thang Nguyen
CEO, DIVINT
In a complimentary consultation, discover how Fabric can transform your business
Thang Nguyen
CEO, DIVINT
In a complimentary consultation, discover how Fabric can transform your business