Business Intelligence Services

BI sits between your data stores and your decision-makers. A complete service covers more than screens:

• Requirements: who needs which answers, how often, and on which device.
• Data preparation: connecting sources and shaping tables suited to reporting.
• The semantic layer: governed definitions of measures and relationships.
• Report and dashboard design, including mobile and embedded views.
• Security, refresh schedules and monitoring.
• Training, support and a process for new requests.

If the main need is custom charts and visual design, data visualization and dashboard development goes deeper on that craft. Reporting built on top of a fresh warehouse usually pairs well with data warehouse development.

A semantic layer is a governed model that tells the BI tool what a customer is, how revenue is calculated, and how tables relate. Analysts then drag fields onto a report without writing SQL or re-creating the logic.

Without it, each dashboard author defines margin differently. With it, a correction made once flows to every report. Star-schema designs, described in the Kimball dimensional modeling techniques (opens in a new tab), are the usual shape for the underlying tables because they are fast and easy to understand.

Decide early where the layer lives: inside the BI tool, in the warehouse, or in a tool-independent layer. Keeping it tool-independent eases a later change of platform, while tool-native models can be quicker to start.

No platform wins in every case. The right choice depends on your existing stack, your users and your appetite for central control. Read each vendor’s own documentation for current features and licensing.

Run a short proof of value with your own data and two or three real reports before committing. Also count the cost of licenses, hosting and the skills your team will need to maintain the choice.

Self-service means business users build or adjust their own reports from approved data. Done well, it frees analysts from routine requests. Done carelessly, it produces hundreds of near-duplicate reports.

A tiered model keeps the balance:

• Approved content: reports owned by the BI team, built on the semantic layer, labeled as trusted.
• Departmental content: reports owned by a team, using approved datasets.
• Personal workspace: exploration that is not shared as an official source.

Add a retirement rule: reports unopened for a set period are flagged for review and removed if nobody objects.

BI concentrates sensitive data in one place, so access control belongs in the design. Row-level security restricts what each person sees, such as a regional manager seeing only their region. Column-level controls can hide fields like salary or national identifiers, and masking can replace them in shared views.

Other practices include single sign-on, groups instead of individual grants, usage and audit logs, and limiting extracts to personal devices. Test security by logging in as a restricted user before launch, not after.

Ask what happens to exported files, since a controlled dashboard can still be downloaded into an unmanaged spreadsheet. For broader controls, see data security and encryption services.

A report no one reads delivers nothing. Plan adoption as part of the project: a named business owner for each dashboard, short training built on real reports, office hours in the first weeks, and a visible channel for questions and requests.

Measure usage and also measure outcomes. Which decisions changed? Which manual reporting tasks stopped? Review these monthly with the business owners and prune what is not working.

• Retail: store managers see sales and stock for their own location only, while head office sees all stores.
• Healthcare administration: wait-time and capacity views for operations leads, with patient identifiers excluded from the reporting model.
• Education: attendance and enrollment dashboards for school leaders with row-level access by campus.
• Professional services: utilization and project margin by partner, refreshed on a weekly cycle.

These are illustrative examples, not Kramate client results.

The data inside your dashboards often includes personal information about customers or staff. Confirm obligations with legal counsel for each region you serve.

• USA: HIPAA covers protected health information, and states such as California apply consumer rights under the CCPA (opens in a new tab).
• UK: UK GDPR applies to staff and customer data in reports; the ICO guidance (opens in a new tab) explains data minimization and access rights.
• Australia: the Australian Privacy Principles (opens in a new tab) under the Privacy Act 1988 govern use and disclosure of personal information.
• Singapore: the Personal Data Protection Act, with practical guidance from the PDPC (opens in a new tab).

Hosting region for the BI service matters for each of these. Support hours matter too: dashboards that executives open at the start of their day need a refresh finished before it.

• User counts and license tiers, which differ by platform.
• Number of data sources and how clean they are.
• Complexity of the semantic model and calculated measures.
• Volume of reports to build or migrate from older tools.
• Security design, including row-level rules.
• Training, support and the capacity of your own team to maintain content.

When pricing business intelligence services, budget separately for platform licensing, build effort and ongoing support. A phased plan, beginning with one department and an approved set of reports, gives a dependable base for estimating the rest.

1. Ask about the semantic layer and how definitions are governed.
2. Request a walkthrough of a security setup, including row-level rules.
3. Check platform neutrality or clear reasons for a recommendation.
4. Ask how they drive adoption, not only how they build.
5. Confirm handover: documentation, source files and training for your staff.

After an NDA and a free consultation, you receive a detailed estimate within 24 hours. A dedicated project manager reports daily on Slack or Teams, and reports and models are demonstrated at the end of every two-week round. You own everything produced. The team works independently or alongside your analysts, as described in our approach.

• Power BI Documentation (opens in a new tab)Microsoft
• Tableau Help (opens in a new tab)Tableau
• Looker Documentation (opens in a new tab)Google Cloud
• Dimensional Modeling Techniques (opens in a new tab)Kimball Group
• California Consumer Privacy Act (CCPA) (opens in a new tab)California Attorney General
• UK GDPR guidance and resources (opens in a new tab)UK ICO
• Australian Privacy Principles (opens in a new tab)OAIC
• Personal Data Protection Commission Singapore (opens in a new tab)PDPC