Business Priorities
Your business priorities and current systems.
Data Consulting
Data Consulting to Build
Your Data Roadmap
For CTOs, data leaders, and business teams, Codiste turns uncertainty about data into clear priorities, informed platform decisions, and a practical investment roadmap. Understand what is holding your data back before committing to the next platform or project. We assess your current environment, evaluate the options, and define what to improve first.
Why get data consulting before you invest?
When teams define the same metric differently, every report needs reconciliation.
When nobody owns a dataset, quality issues move between departments. The business keeps paying for the same unresolved work.
Platform decisions become harder because the underlying requirements remain unclear. A migration may carry inconsistent definitions into a new system. An AI initiative may stall when source permissions and update rules are finally examined.
What is Data Consulting?
Data consulting is the assessment and planning of how an organisation collects, manages, governs, and uses data. It examines business requirements, systems, data quality, ownership, and team capability. The output is a set of recommendations and a roadmap for improving how data supports decisions and operations.
A consulting engagement can answer a focused question, such as which platform to choose, or define a wider data strategy. Codiste connects the recommendations to costs, dependencies, and delivery responsibilities so your team can evaluate the next investment.
Codiste’s Data Consulting Capabilities
Start with a specific decision or combine services into a broader assessment. Each engagement produces findings and recommendations your business and technical teams can review together.
01
Data Maturity and Readiness Assessment
02
Data Strategy, Governance and DataOps Advisory
03
Data Architecture Advisory
04
Data Platform and Technology Selection
05
Pipeline Audit and Modernization Blueprint
Identify pipeline weaknesses and prioritise improvements around their effect on your business operations. We assess technical debt, transformations, dependencies, quality checks, and recovery behaviour. The blueprint covers legacy ETL modernization, migration sequencing, reconciliation, and rollback requirements.
06
AI Data Readiness Consulting
Our Data Consulting Frameworks and Tech Stack
Tools and platforms are evaluated in context, with recommendations based on the work your organisation needs to support.
Apache Spark
dbt
Apache Airflow
Great Expectations
Python
SQL
Scala
Snowflake
Databricks
Microsoft Fabric
Microsoft Purview
Collibra
Power BI
Tableau
Our Data Consulting Process
Each stage answers a defined question and produces a reviewable output. We agree on the schedule after scoping the systems, stakeholders, access requirements, and depth of validation.
1. Define the Priorities
Agree on business outcomes, decisions to support, and assessment boundaries. You receive scope and success criteria once the sponsor and stakeholders are confirmed.
2. Assess the Current State
Review sources, quality, architecture, governance, costs, and team capability. You receive evidence-based findings and a prioritised assessment of the gaps.
3. Evaluate the Options
Compare improvement paths, platform choices, costs, and constraints. You receive recommendations, trade-offs, and a validation plan where trials are needed.
4. Build the Roadmap & Handover
Sequence initiatives by value, risk, and capacity, with milestones, owners, and budgets. After stakeholder review, we hand over deliverables and an implementation briefing.
Clarify Your Data Priorities
Understand what is holding your data back before committing to the next platform or project. We assess your current environment, evaluate the options, and define what to improve first.
Book a 30-min callHow should your data be structured?
The assessment starts with your business priorities and follows the data through the systems and teams that use it. Findings inform the architecture, governance, platform, and cost recommendations. Those recommendations become a phased roadmap with owners, dependencies, and acceptance criteria. Stakeholder review provides a decision point before implementation, while unresolved assumptions remain visible for testing. Your team can see how each proposed change connects to an identified need.
The consulting path
Assessment
Quality, architecture, ownership, and cost.
Options
Improvement options and their trade-offs.
Target-state Design
Governance needs and an investment plan.
Phased Roadmap
Decisions, then implementation handover.
Data Quality and Validation
Use agreed samples and quality evidence to support findings. Keep unresolved assumptions visible for testing.
Ownership and Access
Define stewardship, access principles, approvals, and the teams responsible for implementing and maintaining changes.
Costs and Dependencies
Document cost assumptions, delivery dependencies, and internal capacity when prioritising investments.
Decision Records and Acceptance
Record alternatives, stakeholder decisions, and acceptance criteria before implementation handover.
Data Consulting for Your Next Business Decision
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Plan a Data Strategy
Assess maturity, use cases, skills, and dependencies to define a prioritised roadmap with ownership and investment assumptions.
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Choose a Data Platform
Compare platforms against workloads, governance, costs, and team skills. Define a focused proof of concept where evidence is missing.
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Modernise Legacy Pipelines
Review technical debt, transformations, quality checks, and recovery behaviour. Plan migration sequencing, reconciliation, and rollback requirements.
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Improve Governance and Daily Operations
Clarify data ownership, stewardship, access approvals, and quality responsibilities. Define how changes are tested, released, monitored, and supported.
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Prepare Data for AI
Assess quality, context, permissions, freshness, and evaluation data against the intended AI task. Define a preparation backlog and agent action boundaries.
Data Consulting Planning by Industry
Business requirements, data ownership, access, and operating constraints shape the assessment. We evaluate these in the context of the systems and teams your organisation relies on.
Data Consulting Case Studies
Our published projects show the integration and data-handling decisions that inform our consulting approach.
Plan Your Next Data Investment
Bring us the data decision your team needs to make. We’ll help define the assessment, clarify the options, and plan your next step.
Why Choose Codiste for Data Consulting?
Application and integration experience shape the assessment
We examine how reporting tools, business applications, and AI workflows will use the data. Requirements for freshness, context, and access therefore inform the recommendations from discovery. Projects such as Propizone and EntryPass provide concrete examples of synchronisation and operational data access. We use relevant engineering experience to question assumptions about how systems connect.
Each recommendation has a decision record
We document the finding, proposed change, alternative options, and unresolved assumptions. Your team can evaluate the reasoning and revisit a decision when requirements change.
The roadmap includes the people who will run it
Ownership, skills, access approvals, and support responsibilities are discussed alongside architecture. The handover connects proposed changes to the teams responsible for implementing and maintaining them.
Data Consulting FAQs
Data consulting can include maturity assessment, strategy, architecture advisory, platform evaluation, governance, and modernization planning. Codiste defines the scope around the decisions you need to make. Depending on the engagement, you receive findings, recommendations, cost assumptions, and an implementation roadmap with priorities and responsibilities.
Data consulting focuses on assessment, decisions, and planning; data engineering builds and operates the resulting systems. Consulting may define the requirements for pipelines, integrations, or migration. Your internal team can implement the roadmap, or a separate engineering engagement can be scoped with its own deliverables and commercial terms.
We evaluate your data sources, quality practices, architecture, governance, operations, and team capability against a defined maturity model. Evidence comes from interviews, documentation, system reviews, and agreed samples. You receive a baseline, prioritised gaps, and recommendations connected to the initiative or business outcome you want to support.
We compare platforms against your workloads, integrations, governance requirements, team skills, and total operating costs. Important assumptions may require a focused proof of concept. Recommendations document trade-offs, and relevant vendor relationships or procurement accreditation requirements should be clarified during scoping before a platform commitment is made.
Yes. We assess the proposed task against data coverage, quality, definitions, permissions, freshness, and traceability. For agents that take actions, the review also considers approval boundaries and system access. The output is a preparation backlog and validation requirements that help your team plan the work before development.
We agree on access, approved environments, information handling, and retention before the assessment begins. Where practical, reviews use metadata, masked samples, or read-only access. Your security and privacy stakeholders help identify applicable requirements. A readiness review identifies gaps and remediation needs; formal legal opinions and independent assurance remain separate.
Duration and pricing depend on the assessment scope, number of systems and stakeholders, access availability, and technical validation required. We define the deliverables, milestones, dependencies, and commercial model in the proposal. A focused audit is scoped differently from a wider strategy, and implementation costs are identified separately where relevant.
Yes. We involve the people responsible for your current environment and account for existing tools, knowledge, and operating constraints. The roadmap can guide your internal team, with ongoing advisory support where agreed. Codiste can also scope a separate implementation phase after the consulting recommendations and delivery requirements are reviewed.
Discuss Your Data Consulting Needs with Codiste
Share your current data environment, the decision your team needs to make, and your target timeline. We’ll help define the assessment scope and your next steps.