Data visualization services are the work of turning the data a business already holds into dashboards and reports people read at a glance. Eicra Soft Limited, a Dhaka-based team serving international companies, builds a documented Power BI data model and dashboards inside your own workspace, and a separate quality assurance (QA) lead reconciles every figure to source before anything is published.
Leave after any step; no long-term contract applies. We start with one dashboard the business asks for today. We list every source, measure and refresh, diagnose every slow or wrong report, and cost each route to a working dashboard in your own numbers.
A written verdict follows — a new dashboard, a rebuilt data model, a health check or nothing yet.
Our data visualization services cover the three things a business intelligence (BI) team is hired for: data architecture, a clean semantic model with documented DAX measures over your sources; dashboard development, executive-ready pages built and published in your own workspace; and governance, refresh schedules, row-level security and a runbook, so the dashboards still work after we leave.
Executive and team dashboards are designed page by page with the people who will use them, so each page answers a question someone already asks. Every figure is reconciled to source by a separate QA lead before publishing, and each dashboard is built in your own workspace, never in ours.
Scheduled report packs and paginated reports arrive on time, without anyone exporting data by hand. Subscriptions, alerts and export to PDF or Excel are set up in your own tenant, and each report reads from the same documented measures as the dashboards, so the numbers match.
Workspaces, gateways, refresh schedules, row-level security and app publishing are configured in your Microsoft tenant, so reports refresh on schedule and each viewer sees only their own rows. Every setting is written into the runbook, so your administrator can see how the tenant is set up and change it later.
Power Query transforms feed a star-schema semantic model, and every Data Analysis Expressions (DAX) measure is named, tested and documented. The next developer can read the model without a handover call, and every visual reads from those measures rather than from raw exports, so one number has one definition.
Slow reports are profiled first, then rebuilt where needed with a redesigned model, incremental refresh and lighter measures. Reports kept in Excel or legacy tools can be migrated onto the same model, and each fix is recorded in a change log so you can see what changed and why.
Workspace roles, naming rules and refresh ownership are agreed with you and written into a runbook. The people who will own the dashboards get two hours of recorded training, and our guest access is removed at handover, so the dashboards keep working without depending on us.
Month-end close, cash position and receivables-and-payables dashboards, fed by your ERP and bank exports. Each figure is reconciled to the ledger before the page is published, so the finance team can use the dashboard in the close meeting instead of rebuilding the numbers in a spreadsheet first.
Pipeline, conversion and ad-spend views, fed by your CRM and ad accounts through connectors or the gateway. Deals and campaigns read from one set of documented measures, so sales and marketing look at the same number and spend the meeting on what it means rather than on whose total is right.
Throughput, service-level and exception dashboards, fed by your ticketing and workflow tools. Each page shows where work is waiting and for how long, using timestamps your systems already record, so managers can see a backlog forming before customers notice the delay.
Headcount, staff cost and attendance dashboards, fed by your HR system and payroll exports. Personal data is processed only under a signed data processing agreement, and row-level security limits each viewer to the rows they are allowed to see, tested before the dashboard is published.
Data visualization in Power BI builds the dashboard on a semantic model, not on raw exports. In the example below, a star schema with one fact table and three dimensions carries 31 documented DAX measures; every visual reads from those measures, row-level security decides which region each viewer sees, and a QA lead signs off every figure before publishing.
Microsoft’s Power BI guidance on star schema states: “Star schema is a mature modeling approach widely adopted by relational data warehouses.” The example follows it: one fact table for closed deals and three dimensions for date, customer and region.
Semantic model · star schema
Executive sales dashboard
Sales · fact table One row per closed deal feeds the closed-deals figure and both charts.
Date Month, quarter and fiscal year drive the Month filter, the August figure and revenue by month.
Customer Segment and account owner describe each customer, one row per customer, linked to every deal.
Region Drives the Region filter, deals by region and row-level security: each region sees only its own rows.
31 DAX measures Named and documented; every figure and chart on the dashboard reads from them.
Click a table or the measures, or a number below, to see what they drive
Published in your workspace and refreshed daily at 06:00; Managed Ops watches every refresh.
Illustrative example. Yellow marks the step where a person decides; every visual reads only from the documented measures in the model.
A data visualization project with us runs in five steps. It starts with a free scoping call or a five-day Power BI health check. A two-to-three-week pilot then delivers one dashboard on your own data, and a four-to-six-week production build delivers the semantic model and dashboard set. Managed Ops after handover is optional, and you can stop after any step.
| # | Step | Time | What you get |
|---|---|---|---|
| 01 | Scope | 30 min | One call on your tenant, licences and dashboard; a pilot quote. No data touched. |
| 02 | Diagnose | 5 days | Health check of up to 3 reports or sources, with a written verdict. |
| 03 | Pilot | 2–3 weeks | 1–2 sources, a documented model and one dashboard of up to 3 pages. |
| 04 | Production | 4–6 weeks | Full model, up to 3 dashboards, row-level security, runbook and 30 days’ fixes. |
| 05 | Managed Ops | Monthly · optional | Up to 3 dashboard changes a month and a review call. Cancel any month. |
Prefer a Power BI developer on your team every day? Dedicated developers, three-month minimum
A first dashboard usually takes three weeks. After a five-day health check, we connect one or two sources, build the model and measures, and publish a dashboard you can check against source. Production adds four to six weeks, and each step is priced in writing before it starts.
Not every Power BI problem needs a new dashboard. A clean model with a missing page needs a pilot. Slow reports and wrong totals need a rebuilt model. Four sources joined in Excel need a pipeline from data engineering first. Refresh failures and workspace sprawl need a health check first. Five questions show which fits.
1. Do you already use Power BI?
2. Are the numbers trusted today?
3. How many data sources?
4. Do reports load in under 10 seconds?
5. Who will maintain it after handover?
Power BI in use, numbers trusted, one or two sources: a pilot delivers the missing dashboard in two to three weeks.
How the verdict is decided: Power BI in use and numbers trusted → a new dashboard · numbers not trusted, slow reports or four or more sources → a rebuilt data model · refresh failures or no owner → a health check · no Power BI, one clean source, one user → a spreadsheet, not us.
A data visualization company is judged on the number behind the chart, not the chart. Marketplace freelancers often work alone, with nobody checking their measures. We price each step in writing, keep a QA lead on every delivery and hand over a runbook. Personal data is handled under Article 28 of the General Data Protection Regulation (GDPR).
Outsourcing data visualization is safe when access, transfer and ownership are settled in writing. As a Bangladesh-based company, we sign a mutual non-disclosure agreement (NDA) and a data processing agreement (DPA) before any data moves. We build in your Microsoft tenant and hand the work over as your intellectual property (IP).
Microsoft’s documentation on row-level security (RLS) states: “RLS only restricts data access for users with Viewer permissions.” Workspace roles are therefore set with you, and the rows each viewer sees are tested before publishing.
Three agreements are signed before any data moves, and access is set up in the order shown below. Each agreement names what we may see, where it may be processed and when our access ends, and certifications are listed only when they are actually held.
Six controls apply to every engagement and are written into the contract rather than promised in a proposal. They cover where the work is built, who sees which rows, how each figure is checked, who signs it off, who owns the result and how a failed figure is fixed.
Before you pay for data visualization services, you can check the work yourself. You get three measured commitments and a pilot dashboard built from your own data that you can check line by line. You can also send one slow or wrong report for a free 30-minute review. Client case studies follow as clients agree to be named.
To a first working dashboard on your own data, with every figure reconciled to source.
Reconciled to source by a separate QA lead before publishing, with variances logged with a reason.
Of free fixes after a production build, with a runbook and two hours of recorded training.
Buyers ask twelve questions about data visualization services before they commit. They ask what it costs, what a Power BI consultant does and how a project starts. They also ask about slow reports, Tableau, ownership, where data is stored, confidentiality, takeovers and when a dashboard is not worth it. Each answer follows the prices and terms set out above.
More answersEvery step of our data visualization services has a fixed price on the cards at the top. The five-day health check is credited to the pilot, which delivers one dashboard on your own data in two to three weeks. Production is quoted after the pilot, and Managed Ops is optional.
Data visualization services design, build and maintain the dashboards and reports a business reads its numbers from. With us that means a documented Power BI data model, dashboards published in your own workspace, scheduled reports, row-level security and a runbook, with every figure reconciled to source by a separate QA lead before anyone sees it.
A Power BI consultant designs the semantic model behind your reports, with tested DAX measures over your Structured Query Language (SQL) databases and other sources. The consultant builds the dashboards and scheduled data analytics reports on top, then sets up workspaces, refresh, row-level security and training, and reconciles every figure to source.
A dashboard project starts with a free call, and every later step is priced in writing before it begins, so you can stop after any step without paying for work you did not ask for. The steps run in this order.
Yes, and it is the most common job we take. Slow reports are profiled and usually rebuilt with a new semantic model, incremental refresh and lighter measures. Wrong numbers are traced to source, and dirty source data goes to data cleansing. A change log records every fix.
Yes, Tableau too. Power BI is our main platform and every price on this page is for Power BI, but where your team already licenses Tableau, we build there under the same rules. We do not recommend switching tools to fit us.
Your data stays in your own Microsoft tenant. Models, dashboards and gateways are built there, never on our side, and our team in Dhaka works through guest accounts with the least workspace role needed. Personal data is processed only under a signed DPA, and international transfers use standard contractual clauses or the instrument your jurisdiction requires.
You do. The semantic model, DAX measures, dashboards, gateways and runbook are built in your Microsoft tenant and stay yours under the contract. We work through guest accounts with the least workspace role needed and remove our access at handover, so nothing depends on us.
Confidential data is protected by contract first. A mutual NDA is signed before we see any report, model or dashboard, a DPA covers any personal data, and row-level security decides which rows each viewer sees, tested before publishing. Credentials never leave your accounts, and our guest access is removed at handover.
Yes. A takeover starts with the five-day health check, which reviews the tenant, workspaces, existing model and slow or wrong reports. It ends in a written verdict: health fixes, a rebuilt model or a new dashboard. You can stop after the health check without paying for anything else, and its fee is credited to the pilot.
After you book, a 30-minute scoping call confirms the dashboard you need, your tenant and your licences. You then give guest access to up to three reports or sources, the five-day health check runs, and a written verdict follows with a pilot quote when the sources and licences are known. Nothing is built until you approve that quote.
A dashboard is not worth it for one user with one clean source and no Power BI; a spreadsheet or a report pack does that job, and we say so on the call. It is also premature when nobody trusts the numbers yet, because the data model has to be rebuilt before any dashboard is.
Start with a free 30-minute scoping call or the five-day health check.
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