All Case Studies
Our business intelligence clients stop arguing about which revenue number is correct metrics
Two recent business intelligence engagements built on one governed semantic model. Full metrics under MNDA; workbook walkthrough on a scoping call.
Cloud and Data engagement,
BI and analytics lead
Dcrayon replaced our tangle of exported spreadsheets with one governed Power BI model. Every dashboard now traces to a defined measure that finance signs off on.
Business intelligence build: star-schema warehouse, dbt-modeled measures, and a certified Tableau workbook with row-level security. Definitions live in a shared data dictionary.
Read Cloud and Data engagement's Case StudyMid-market cloud and data brand,
BI and data warehouse lead
Our dashboards contradicted each other for more than a year. Dcrayon rebuilt the semantic layer so sales, finance, and operations read the same revenue figure.
Business intelligence build paired with a cloud warehouse migration. A free Growth Intelligence readout mapped every existing report to its true source before cutover.
Read Mid-market cloud and data brand's Case StudyWhy choose Dcrayon for Business Intelligence
Dcrayon has shipped 200+ solutions engagements for 60+ active retainers since 2016, from our Delhi HQ and Sheridan, Wyoming office. Our teams build on Power BI, Tableau, and the major cloud warehouses, with AWS, Azure, and GCP-certified architects on staff. AI-first since the 2024 pivot.
A BI architect who owns your semantic layer
No juniors learning DAX or LookML on your budget. The architect who models your data stays on the account.
A five-axis Score before you commit
A written diagnostic and fixed estimate up front. You see exactly which reports and models we would fix before you sign anything.
AI-assisted analytics as standard
Every engagement includes AI-assisted analytics: anomaly alerts on key metrics, forecast lines on trends, and natural-language querying where your tools support it.
A monthly readout finance can act on
Weekly sessions and a monthly readout tied to one reporting metric. Numbers finance can read without an analyst translating them.
HOW WE WORK
How Dcrayon works with the brands we partner with
A short film on how we work: the people you deal with, how we report, and the results we hold ourselves to.
What we build for business intelligence
Three layers that turn scattered exports into one set of numbers every team quotes.
Step 1: A governed semantic layer
dbt models and metrics Metrics defined once in dbt, tested and versioned, so revenue means the same thing in finance, sales and the board pack.
Step 2: Dashboards people actually open
Tableau, Power BI, Looker A small number of dashboards built around decisions somebody makes weekly, rather than a library nobody maintains.
Step 3: Self-serve that holds up
Metabase and governed access Row-level permissions, certified datasets and documentation, so teams answer their own questions without inventing new numbers.
Technical business intelligence practices we build in
What ships by default on every Dcrayon business intelligence engagement
Each practice below maps to a real part of your analytics stack, built and verified by the BI architect on your account.
Version-controlled metric logic
Every metric and dashboard change ships in Git: a definition diff, before and after query results, a data dictionary entry, and a note in the docs site.
AI-assisted analytics
Dcrayon AI watches your key metrics for anomalies, flags dashboard drift, and writes plain-English summaries of what moved and why.
Power BI and Tableau cost control
We right-size Power BI Premium capacity and Tableau seats and cut warehouse spend by pruning heavy queries.
You see cost per active dashboard user, not just a licence bill.
Row-level security and governance
Row-level security, certified datasets, and access roles are set from the start, with SOC 2, ISO 27001, and GDPR-aware controls applied to every report.
Three proprietary tools we apply to every Business Intelligence engagement
Score, Sequence, Repair. The analytics maturity diagnostic, the quarter-long roadmap, and the AI-assisted toolkit we run on every business intelligence engagement.
Growth Intelligence (business intelligence axis)
A 150-point read across your data stack. The business intelligence layer scores your warehouse model, your semantic layer, refresh reliability, DAX and measure hygiene, and how many people actually open the dashboards. Free on every proposal call.
Dcrayon Growth Engine (business intelligence sequencing)
The roadmap that sequences your business intelligence work back to one reporting metric you pick, from data model to a dashboard people open every morning.
Dcrayon AI (business intelligence toolkit)
Internal toolkit that audits your dbt models and dashboards, finds broken or duplicated metrics, and writes a prioritized fix list finance can budget.
How Dcrayon runs business intelligence work
Three repeatable practices that make each reporting cycle build on the last.
Step 1: Score
A free Growth Intelligence readout. We rate your reporting setup from 0 to 100, checking whether the numbers reconcile across Power BI, Tableau, and your finance exports, and hand you the list of gaps. No follow-on commitment.
Step 2: Plan
A written 90-day plan built around one operational metric you name, like on-time delivery or gross margin. A senior BI engineer designs the data model and each report. Either side can end the SoW at day 90; no annual lock-in.
Step 3: Compound
A weekly working call plus a monthly summary your finance team can read. The work stacks: a clean data model in the first cycle earns the dashboards people trust in the second, which support the alerts and scheduled reports in the third.
Get a readout of your reporting setup
A written score of your current reporting, naming which numbers disagree and why, plus a fixed estimate.
Other Cloud and Data solutions
Sibling Dcrayon services inside the Cloud and Data category. Programs clients often layer alongside Business Intelligence.
WHY DCRAYON
Why finance teams keep the reporting with us
Four commitments behind every business intelligence engagement.
One definition, written down
Every metric has an owner and a definition in the semantic layer. Disagreements get settled in the model, not in a meeting.
The architect who models it stays
No juniors learning DAX or LookML on your budget. The architect who builds your semantic layer keeps running it.
Adoption is the measure
We report on which dashboards are actually opened. A build nobody uses is a failure, however clean the model underneath is.
Your models, your warehouse
Everything ships in your warehouse and your repository. Leave at any point after 90 days and the work stays with you.
Real client work, with the receipts
200%
Improvement in conversion performance
Proven Water Industries
Proven's growth on Amazon over the engagementDcrayon's work on Proven's Amazon account has run as a long-term growth programme rather...
Keratine Professional
What is in place on Keratine Professional's accountOn Amazon.in today, the brand's lead listings name the product type, the hair concern...
3,400%
Sales growth on Amazon India
GetSetNova
Sales up 3,400% on Amazon IndiaOver the engagement, GetSetNova's sales on Amazon India are up 3,400%, and the brand holds Amazon Best...
McCormick & Company
What changed on McCormick's front endThe front end now loads non-essential scripts after the main content, runs third-party tags through...
Roundglass
What changed for Roundglass's HR team, IT and new employeesAccount creation, group membership and licence assignment now follow the...
GRYT Health Labs
What GRYT shoppers can do on the storeShoppers can check the brand's licence and ownership details, compare single units with packs of...
Daddy of Tastes
What the Daddy of Tastes kitchens and riders work withCustomers can order from the full menu, pin their exact location, pay through...
Instacertify
What Instacertify's visitors could doVisitors could search for a certification from the first screen, see two clear next steps, and move...
Northern Tile Distributors
The storefront delivers a clean shopping experience on both desktop and mobile. Page load times improved significantly, the add-to-cart rate...
RAA Logistics
What RAA's customers and team have nowProspective customers can find the exact service they need, read what it covers, see who runs the...
The Business Intelligence Score is free. The written plan is yours to keep.
Across our 60+ active solutions retainers, the median 12-month cost we measure for teams still running the business on manual spreadsheet reports lands in the Rs 6L to Rs 90L band. Book the scoping call to size yours.
Free five-axis Growth Intelligence on your BI and reporting stack
Written plan tied to one reporting metric you pick
Mutual exit clause in every SoW, no annual lock-in
The BI architect on your account from the first session
Business Intelligence FAQs
We start with the free Score readout, then scope a plan you approve before any build begins. Once the SoW is signed, we move into data modeling and semantic-layer work.
Both. Some clients use us as their full analytics team; others use us as the BI architect and escalation layer for an in-house data team. We scope per account.
Most business intelligence engagements start at Rs 4 to 8 lakhs per month (India) or USD 6 to 15 thousand per month (global). That covers the data model, the Power BI or Tableau build, and the reporting. Audit-only engagements start lower.
Yes. A free five-axis Score readout on your reporting stack on every proposal call. No follow-on commitment required.
Ready to Grow Your Business?
Get expert digital marketing that delivers measurable results. Free consultation available.
We will review how your search, paid and marketplace channels are performing, and point out the gaps costing you the most right now.
You will finish the call knowing what to fix first, whether or not you work with us.