Keep your data environment reliable, useful, and improving

The first dashboard is rarely the last requirement

Once analytics becomes part of everyday operations, the environment keeps changing. New KPIs appear, source systems change, users request new reports, refreshes fail, APIs evolve, and leadership asks new questions.

• Internal teams have more BI requests than they can deliver
• Power BI issues are handled reactively instead of proactively
• Data pipelines or APIs fail and ownership is unclear
• Reports need continuous changes as the business evolves
• New systems need to be integrated into existing reporting
• Documentation is incomplete or outdated
• Critical knowledge sits with one employee or contractor
• The organisation needs specialist skills occasionally, not full-time

Datazeb provides a flexible layer of specialist capability around the environment so analytics can continue to evolve without becoming a bottleneck.

What ongoing support can include

Flexible engagement models

Choose the level of support that fits the workload

A broader support model than a typical Power BI retainer

One partner across the full data-to-decision environment

Many support arrangements fail because one vendor owns the dashboard, another owns the database, and nobody owns the integration between them.

Datazeb can support the connected environment across:

1. Source Systems
2. Data Pipelines
3. Databases
4. BI / Reporting
5. AI & Automation

This reduces the number of hand-offs when an issue crosses multiple layers.

Typical monthly support requests

• Add a new KPI or dashboard page
• Connect a new API or business system
• Investigate why a refresh or scheduled job failed
• Improve a slow Power BI model
• Update row-level security or user access
• Resolve differences between report totals and source systems
• Change business rules or DAX calculations
• Create a new database view or transformation
• Modify an automation workflow
• Add a new knowledge source to an AI assistant
• Document an existing process or data model
• Review whether a new request should be solved with BI, automation, or AI

Proactive improvement

Support should do more than wait for something to break

Where the engagement allows, Datazeb can help identify improvements before they become urgent.

• Performance and model optimisation opportunities
• Fragile manual reporting processes
• Repeated support issues that should be automated
• Data quality patterns
• Unused or duplicated reports
• Integration dependencies and failure risks
• Governance and access gaps
• New AI or automation opportunities grounded in existing processes

This shifts the relationship from reactive technical support toward continuous analytics improvement.

Environment onboarding

Start by understanding what already exists

Before taking ongoing responsibility, Datazeb should map the current environment so support does not begin with assumptions.

• Data sources and business systems
• Databases and pipelines
• Power BI workspaces, reports, datasets, gateways, and refreshes
• APIs and integrations
• Automation workflows
• Access and security model
• Known issues and recurring failures
• Documentation and ownership
• Current backlog and business priorities

The output can become a shared operating picture for future support and improvement.

Service continuity and knowledge retention

Reduce dependency on one person knowing how everything works

Analytics environments often become risky when critical knowledge exists only in one employee, contractor, or developer’s head.

A managed support relationship can improve continuity through:

• Structured documentation
• Shared issue and change history
• Repeatable deployment practices
• Clear ownership of recurring tasks
• Knowledge transfer to client teams
• Documented source-system and data dependencies

Support for internal teams

Add specialist capability without replacing your team

Datazeb can work alongside BI developers, analysts, IT teams, operations teams, finance teams, or external technology partners.

The goal can be to remove a backlog, provide deeper technical expertise, cover a capability gap, or accelerate delivery while internal staff retain ownership.

• Backlog acceleration
• Senior technical escalation
• Architecture review
• Complex DAX / SQL / API support
• Temporary capacity during busy periods
• Peer review and quality assurance
• Mentoring and knowledge transfer

Why Datazeb for managed support

Service levels and response expectations

Set expectations clearly

Commercial proposals can define:

• Monthly capacity or support hours
• Priority categories
• Expected response windows
• Planned development cadence
• Escalation path
• Availability across agreed time zones
• What is included vs separately scoped

This creates confidence without overpromising.

Technologies Datazeb can support

• Power BI – Desktop, Service, Report Server
• Microsoft Fabric and Azure ecosystem
• SQL Server, PostgreSQL, Oracle, MySQL
• Python data pipelines and scripts
• REST APIs and custom integrations
• AWS environments where relevant
• Power Automate and n8n
• ERP, CRM, accounting, POS, healthcare, and other business platforms
• RAG, AI assistants, chatbots, and agentic workflows

How managed support works

1. Assess
   Review the current environment, recurring issues, priorities, ownership, and expected support demand.
2. Onboard
   Document systems, access, dependencies, key reports, pipelines, workflows, and escalation paths.
3. Prioritise
   Maintain a shared backlog based on business impact, urgency, and available capacity.
4. Deliver
   Complete enhancements, investigate issues, provide advisory, and communicate progress clearly.
5. Improve
   Identify recurring problems, performance opportunities, automation candidates, and future roadmap priorities.

Frequently asked questions