Use case · Enterprise · All Departments
Enterprise Data Analysis Assistant
This proposed Enterprise Data Analysis Assistant would help employees across departments investigate operational, financial, and commercial questions using approved enterprise data. Built with BrainShift Workspace, BrainShift Studio, and BrainShift Gateway, this medium-complexity application would combine natural-language requests with governed queries, transparent calculations, and analyst review.
This page describes a proposed application of the BrainShift platform. It is not a description of a specific customer deployment.
Business challenge
Department directors often receive spreadsheets and dashboards that disagree because their reporting periods, filters, or metric definitions differ. Answering a seemingly simple question about rising expenditure can require locating extracts, checking joins, and asking finance or technology teams to reproduce calculations.
Employees may understand the business question but lack SQL skills or knowledge of database structures. Meanwhile, analysts spend time clarifying requests and producing recurring comparisons rather than investigating exceptions. Broader data access introduces additional risks when payroll, customer records, or commercially sensitive details appear in results.
How BrainShift solves it
BrainShift Studio would be used to build an analytics application that maps business language to approved datasets and metric definitions. It could generate read-only queries, apply validation rules, and return summaries with source references, filters, calculation logic, and freshness information. Ambiguous questions would trigger clarification rather than an unsupported answer.
Employees would interact through BrainShift Workspace, while BrainShift Gateway would govern model access, routing, and usage costs. Configured data connections would enforce source permissions and query limits. The assistant would support investigation and drafting, not autonomous operational decisions or unrestricted database execution.
How it works
Step-by-step workflow
- 01
1. Define the question
The employee specifies a comparison, trend, or exception; the assistant clarifies dates, organizational scope, and metric meaning.
- 02
2. Identify permitted data
The application selects approved datasets and checks the employee’s access, available fields, refresh dates, and relevant definitions.
- 03
3. Prepare a query
It drafts a read-only query against approved views, applying configured row limits, join rules, and resource constraints.
- 04
4. Validate the analysis
Checks flag missing values, inconsistent units, duplicate records, and mismatched periods before conclusions are drafted.
- 05
5. Explain the findings
The assistant presents comparisons and possible drivers alongside query details, caveats, and supporting records where access permits.
- 06
6. Review and share
An authorized employee verifies the interpretation and approves sensitive sharing or any consequential action through established processes.
In practice
Example requests
"Why did departmental spending rise last quarter?"
The assistant compares approved expense categories and periods, highlights contributors, and separates observed changes from unverified explanations.
"Compare regional sales without exposing customer details."
It aggregates permitted sales records by region, suppresses restricted fields, and explains filters and currency assumptions.
"Reconcile these two monthly reports."
It checks reporting dates, definitions, and included records, then identifies differences requiring owner review.
BrainShift components
What each module does
BrainShift Workspace
Provide a secure employee interface for analytical questions, follow-ups, and review of supporting evidence.
BrainShift Studio
Build the analytics application, including schema mappings, query generation, validation checks, and result explanations.
BrainShift Gateway
Control model access, route analytical requests to approved models, and govern model usage and costs.
Enterprise integrations
Systems it can connect to
Configurable integration options, confirmed during implementation.
- SQL Server: Configurable read-only access to curated reporting views.
- SAP: Approved financial and operational extracts through configured interfaces.
- Microsoft Dynamics: Permitted sales, service, and pipeline data for comparisons.
- SharePoint: Approved reporting spreadsheets and metric-definition documents.
- Identity providers: SSO and identity mapping for access enforcement.
Data sources
- Curated warehouse tables and reporting views
- Approved ERP transaction extracts
- CRM opportunity and service records
- Departmental reporting spreadsheets
- Metric dictionaries and fiscal calendars
Business outcomes
Potential benefits
Faster investigation
Could reduce repeated handoffs for routine departmental questions.
More consistent comparisons
Shared definitions could reduce conflicting interpretations of the same metric.
Traceable conclusions
Source references and calculations could make findings easier to verify.
Earlier quality checks
Validation could expose data issues before reports circulate.
Greater analyst focus
Routine query support could free specialists for complex investigations.
Suggested KPIs
Security and deployment
The application can be scoped for sovereign, on-premises, or private-cloud deployment. SSO, role-based access, source-level permissions, and audit trails should cover requests, queries, and exports. Read-only credentials, sensitive-field masking, retention controls, and approved model routes should be configured before production use.
Human oversight
Data owners approve datasets and metric definitions; analysts review complex calculations and disputed interpretations. Financial commitments, personnel decisions, sensitive disclosures, and other high-impact actions always require authorized human review and approval. The assistant should distinguish observed relationships from proven causes.
FAQ
Frequently asked questions
Can it query every enterprise database?
No. Access would be limited to explicitly configured sources, approved views, and the employee’s permissions.
How are incorrect queries handled?
Configured checks would reject unsafe or invalid queries and flag uncertain calculations for analyst review.
Does it replace existing dashboards?
It would complement dashboards by supporting follow-up questions, reconciliations, and explanations against governed data.
Can it change records or approve decisions?
This proposed scope is read-only; consequential decisions remain with authorized people.
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