Data Analytics Company for Reports and Dashboards
Business Data Turned Into Monthly Answers
Data analytics services are the work of turning the numbers a business already has into reports and dashboards people act on. Eicra Soft Limited, a Dhaka-based team serving international companies, connects your CRM, ERP and HR systems, spreadsheets and ad accounts, then builds pipelines, data models and Power BI or Tableau dashboards, each reconciled to source and checked by a QA lead.
Stop after any step; nothing runs on a long-term contract. Our analysts map one business question with the people who ask it today. They list every data source, count every gap and manual step, and cost each route in your own numbers.
The written verdict names one route — a report, a dashboard, a data pipeline or nothing yet.
30 minutes 01 Scope · free call
5 days 02 Diagnose · $99, credited to the pilot
2–3 weeks 03 Pilot · $1,200 fixed
4–6 weeks 04 Production · from $3,600, quoted after the pilot
Monthly 05 Managed Ops · $999 a month, optional
What is included in our data analytics services?
Our data analytics services include six deliverables: a written data map, a cleaned and documented data model, one dashboard or report pack in your own Power BI or Tableau account, a QA check against your source systems, a runbook with refresh and ownership notes, and a monthly review. You receive numbers you can defend, not a slide deck.
Microsoft’s Power BI documentation on data refresh states: “Knowing how to refresh the data is often critical in delivering accurate results.” Every data model therefore ships with a runbook that names who refreshes what, how often, and what to do when a source changes.
Data map and question list
Every source, owner, refresh rate and gap is written down before any model is built. The map lists the business questions in the words of the people who ask them, so each later dashboard page traces back to one question and one named owner.
Cleaned, documented data model
Tables and measures are named, deduplicated and documented, so the next analyst understands them without a handover call. Each measure carries its definition and source field, and every transformation step is written in the runbook, so a second analyst can rebuild the model and get the same figures.
Dashboards in your own account
Dashboards are built in Power BI or Tableau inside your own workspace and licences, so nothing depends on our accounts. Your administrators control sharing and access from day one, and if you stop working with us, every page, dataset and refresh schedule stays exactly where it is.
QA against source systems
Every figure is reconciled to the system it came from before you see it, and each difference is logged with a reason. A QA lead, not the analyst who built the report, signs off each delivery, so errors are caught by a second person before a decision rests on them.
Runbook and refresh ownership
The runbook names who refreshes each dataset, how often it runs and what to do when a source changes. It is handed over with the dashboards, so a refresh failure on a Monday morning has a written fix and a named owner rather than a support ticket sent to us.
Monthly review call
One call a month covers what the numbers say and what to change. The review checks refresh failures and open variances, agrees any new question for the next month, and records each decision in the change log, so the dashboards keep answering the questions people ask now.
Not included: BI licences and cloud costs (in your name) · data entry or manual clean-up of paper records · reports on sources outside the agreed list, priced in writing first.
Finance and cash reporting
Monthly P&L, cash position, receivables and payables, pulled from your ERP and bank feeds. Each figure is reconciled to the ledger before the pack goes out, so finance teams can use the report in a board meeting without rebuilding the numbers in a spreadsheet first.
Sales & marketing
Pipeline value, conversion rates and ad spend by channel, joined from your CRM and ad accounts. Deals and campaigns are matched on one set of definitions, so sales and marketing stop arguing about whose number is right and start discussing what it says about next month.
Operations and service levels
Throughput, service-level and exception reports, built from your ticketing and workflow tools. Each report shows where work is waiting and for how long, using the timestamps your systems already record, so managers can see a backlog forming before customers notice the delay.
HR & payroll
Headcount, staff cost and attendance analytics from your HR system and payroll exports. Personal data is processed only under a signed data processing agreement, and access to each page is set by your own administrators inside your workspace, so payroll detail is seen only by the people you choose.
How does your data become a checked report?
Your data is turned into a checked report in five steps: we connect your sources through connectors or an application programming interface (API); a pipeline cleans and joins the data; a documented data model is built; the QA lead reconciles every figure to its source; and the report or dashboard is delivered in your own Power BI or Tableau workspace.
Five steps · sample monthly revenue report
What the step does · its result
Your sources
Connected through connectors or an API.
CRMERPSpreadsheetsAd accounts
Data mapEvery source, owner, refresh rate and gap is written down before any model is built.
4,812
Closed deals pulled from the CRMSample source pull, September
Pipeline
Each source is pulled, cleaned and joined.
Connectedeach source through connectors or an API
Cleaned and joinedone set of tables for the data model
One set of clean tablesthe input for the data model
Data model
One the next analyst can reproduce.
Tables namedMeasures namedDeduplicatedDocumented
Model refreshedCurrency and fiscal calendar applied
QA reconciliation · a person decides
Every figure is reconciled to its source; differences are logged.
Reconciled to ERP0.3% variance flagged, 3 deals
QA sign-offQA lead approved · 2 fixes logged
0.3%
Variance flagged on 3 dealsApproved after 2 fixes were logged
Report or dashboard
Built in your own workspace and licences.
Power BITableauYour workspaceYour licences
12
Pages in the monthly revenue reportEvery figure traced to source
Click a step, or a number below, to switch the result
Managed Ops: refresh checks, a monthly report pack and one review call.
Illustrative flow. Yellow marks the step where a person decides; every figure is reconciled to its source before you see it.
How does data analytics work, step by step?
Data analytics with us moves from question to dashboard in five steps. A free 30-minute scoping call or a five-day diagnostic defines the question. A pilot answers it in two to three weeks. A four-to-six-week production build then delivers the pipeline, data model and dashboards, and Managed Ops after handover is optional. You can stop after any step.
Data analytics timeline
| # | Step | Time | What you get |
|---|---|---|---|
| 01 | Scope | 30 min | A call on your question; known sources get a pilot quote. No data touched. |
| 02 | Diagnose | 5 days | Up to 3 sources reviewed and a written verdict: report, dashboard, pipeline or nothing yet. |
| 03 | Pilot | 2–3 weeks | One question answered from 1–2 sources: a report, reproducible queries and a go/no-go note. |
| 04 | Production | 4–6 weeks | Documented model, up to 3 dashboard pages in your account, runbook and 30 days’ fixes. |
| 05 | Managed Ops | Monthly · optional | Up to 3 reports a month, refresh checks and one review call. Cancel any month. |
Prefer a dedicated analyst instead? Three-month minimum
How long does a first pilot take?
A first pilot usually delivers its written answer in three weeks. After the five-day diagnostic, we spend two to three weeks connecting one or two sources, building the model and answering the question with numbers you can check. Production, with pipelines and dashboards, adds four to six weeks, and each step’s price is on the cards at the top.
Runbook Refresh and ownership notes for every data model, handed over with the dashboards
Tools Power BI, Tableau, Structured Query Language (SQL), Python
Communication Weekly call, shared channel, change log
Sources CRM, ERP, spreadsheets, ad accounts via connectors or API
QA Every figure reconciled to source
Hosting Your workspace, your licences
Do you need a report, dashboard or pipeline?
Not every data analytics question needs a dashboard. A question asked once needs a report. A question a team asks every week needs a dashboard from our data visualization service. Data joined from four or more systems needs a pipeline built by data engineering first. Answer five questions and the verdict shows which fits.
1. How often is the answer needed?
2. How many data sources?
3. Does the data need cleaning first?
4. Who uses the answer?
5. Rows per month?
You need a dashboard
Asked weekly or daily by a team: a production build with a documented model in your Power BI or Tableau workspace.
Sample QA log · monthly revenue report
1
Source pulledCRM: 4,812 closed deals, September
2
Reconciled to ERP0.3% variance flagged, 3 deals
3
Model refreshedCurrency and fiscal calendar applied
4
QA sign-offQA lead approved · 2 fixes logged
5
Report sent12 pages · every figure traced to source
Illustrative log
Yellow = a person decides
Every figure traced to source
Every step logged
How the verdict is decided: needed once with one or two sources → a report · needed monthly or daily by a team → a dashboard · four or more sources or heavy cleaning → a pipeline first · one user, one clean source, under 10k rows → a spreadsheet, not us.
Why choose us as your data analytics company?
A data analytics company builds the reports and dashboards a business decides with. We reconcile every figure to its source, keep a QA lead on every delivery and write a runbook for every data model. Personal data is handled under Article 28 of the General Data Protection Regulation (GDPR). Outsourced analytics usually fails in the number, not the chart.
The Government Data Quality Framework states: “Poor or unknown quality data weakens evidence, undermines trust, and ultimately leads to poor outcomes.” That is why a figure that fails reconciliation is reworked free of charge. Every variance is logged with a reason before a report reaches you.
Without a checked process
!!!!!
- A dashboard that looks right and is wrong by 8%
- A model only the freelancer understood
- Dashboards hosted on the vendor’s account
- Hourly quotes that grow with every new source
With Eicra Soft Limited
QA sign-off
Figures checked142Variances3Fixed3Signed byQA lead
Illustrative example
- Every figure reconciled to its source before delivery
- Documented model and runbook; a second analyst can reproduce it
- Built in your workspace and licences from day one
- Fixed prices per step; new sources priced first as a change
Is it safe to outsource data analytics?
Outsourcing data analytics 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 work read-only in your Power BI or Tableau workspace and hand over every model as your intellectual property (IP).
Which agreements are signed, and when?
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.
NDA — mutual, signed before we see a single data source or dashboard.
DPA — the processor contract Article 28(3) of the GDPR requires, before any personal data is processed.
Data transfers — standard contractual clauses, an International Data Transfer Agreement or local transfer clauses, signed before personal data moves.
Access — read-only connections to source systems where possible; credentials held in your accounts.
Certifications — named here only when held; this page claims none.
Which controls, IP and rework terms apply?
Five controls apply to every engagement and are written into the contract rather than promised in a proposal. They cover where the work is built, how each figure is checked, who signs it off, who owns the result and how a failed figure is fixed.
Workspace Dashboards and models built in your Power BI or Tableau tenant, never ours.
Reconciliation Each delivered figure is traced to its source system, and each variance carries a written reason.
QA sign-off No report reaches you until a QA lead has approved it.
Ownership Queries, data models, dashboards and the runbook belong to you under the contract; our access ends at handover.
Rework A figure that fails reconciliation is reworked free; a new source is priced as a change request first.
What proof do you get before you pay?
Before you pay for data analytics, you can judge the work on evidence. You get three measured commitments and a pilot that answers one of your own questions from your own data. You can also send one report you already use for a free 30-minute review. Case studies with client numbers follow as clients agree to be named.
Every figure
Reconciled to its source system before you see it, with every difference logged with a reason.
30 days
Of free fixes after each production build, plus the runbook and handover training.
1 question
A fixed-price pilot answers one business question from your own data in two to three weeks.
Case studies: results with client numbers appear here once each client agrees to be named. On the scoping call, ask for references from your industry.
Free 30-minute report review Send one report or dashboard you do not trust. A written note comes back on what is wrong, what fixing it takes and whether the fix is worth it, whether or not you hire us.
What do buyers ask a data analytics company?
Buyers put twelve questions to a data analytics company before they start. They ask what it costs, what it covers and how a project starts. They also ask where data is stored, who owns the models, how confidential data and takeovers are handled, and when analytics is not worth it. Each answer uses the prices, pilots and reconciliation rules set out above.
Reviewed by Mohammad Nazrul Islam, Managing Director, Eicra Soft Limited.
How much do data analytics services cost?
Each step of our data analytics services has a fixed price, shown on the price cards at the top. The diagnostic fee is credited to the pilot, and the pilot answers one business question in two to three weeks. Production is quoted in writing once the pilot is done, and Managed Ops runs up to three reports a month.
What are data analytics services?
Data analytics services turn the data a business already has, in its CRM, ERP, spreadsheets and ad accounts, into monthly report packs, Power BI or Tableau dashboards and data pipelines. Ours are fixed-price and delivered in your accounts: every figure is reconciled to its source, a QA lead signs off each delivery and the data model is documented.
What does a data analytics company do?
A data analytics company collects the data a business already produces, runs it through data cleansing, models it and delivers reports and dashboards that answer specific questions: revenue by product, cost per hire, cash by week. The good ones also document the model and reconcile every figure to its source, so the numbers survive the analyst leaving.
Does data analytics suit a small business?
Yes, when one question is worth answering with numbers. A fixed-price pilot answers it from your own data in two to three weeks. A question asked once needs a report, not a dashboard, and Managed Ops keeps up to three reports running each month; every price is on the cards at the top.
Is this analytics consulting or delivery?
Data analytics consulting tells you what to build; our data analytics services build it. Every engagement ends with a working report, dashboard or pipeline in your account, reconciled and documented, not a recommendation deck. If a question only needs advice, the five-day diagnostic says so and no production build is proposed.
How does a data analytics project start?
A project starts with one question and a free call, and every later step needs your written approval 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.
- A 30-minute scoping call defines the question and the sources.
- The five-day diagnostic reviews up to three sources and gives a written verdict.
- A fixed-price pilot answers the question from your own data.
- Production follows only if the pilot shows it is worth building.
Where is our data stored and processed?
Your data stays in your own systems and your own Power BI or Tableau workspace. Our analysts in Dhaka work through read-only connections where possible, with credentials held in your accounts. A data processing agreement under Article 28 of the GDPR is signed before any personal data is processed, and our access ends at handover.
Who owns the dashboards and data models?
You do. Queries, data models, dashboards and the runbook belong to you under the contract, and everything is built in your own Power BI or Tableau tenant, never ours. Our access ends at handover, so a second analyst or your own team can take over the work without asking us for files.
How is confidential data protected?
Confidential data is protected by contract before it is protected by tools. A mutual NDA is signed before we see a single source, a DPA covers any personal data, and transfers use standard contractual clauses or a local equivalent. Work is read-only where possible, and this page claims no security certification that is not held.
Can you take over existing dashboards?
Yes. A takeover starts with the five-day diagnostic, which reviews the existing models, sources and refresh schedule and lists what is undocumented or unreconciled. You then receive a written verdict: keep, fix or rebuild. Fixes are priced in writing before any work starts, and your dashboards keep running in your workspace during the handover.
What happens after I book a diagnostic?
After you book, a scoping call confirms the question, the sources and who holds access. You then share read-only access to up to three sources, our analysts review them for five days, and you receive a written verdict naming one route: a report, a dashboard, a data pipeline or nothing yet.
When is data analytics not worth it?
Data analytics is not worth it for one user with one clean source and under 10,000 rows; a spreadsheet does the job. It is also premature when the source data is incomplete or not yet recorded. The diagnostic says so in writing rather than proposing a build you do not need.
Start with a free 30-minute scoping call or the five-day diagnostic.