The short answer
Both tools turn raw data into charts your team can read every morning. The real difference is where your data already sits and who needs to see the dashboard. Google’s free tool, called Looker Studio from 2022 and renamed back to Data Studio in April 2026, is built around Google Sheets, BigQuery, GA4 and Google Ads, and you share a dashboard the way you share a Google Doc. Microsoft Power BI is built around Excel, SQL databases and a proper data model, and it charges per user once you share.
For most Indian SMEs with under 20 people looking at reports, the cheapest working setup is: data lands in a Google Sheet or a small database every night, and a free Data Studio dashboard sits on top. When you have several lakh rows, messy joins across Tally, a CRM and an ERP, or finance teams who live in Excel, Power BI usually earns its licence fee.
Side-by-side comparison for Indian businesses
| Looker Studio / Data Studio | Power BI | |
|---|---|---|
| Cost to build | Free | Power BI Desktop is free to build in |
| Cost to share | Free with Google accounts; Pro listed at $9 per user per project per month | Pro ₹1,165 and Premium Per User ₹1,995 per user per month, paid yearly, GST extra (Microsoft India page, Nov 2026) |
| Who needs a licence | Nobody, on the free tier | Both the publisher and every viewer, outside Premium/Fabric capacity |
| Google Sheets | Native, live connector | Possible via connectors or exporting; less smooth |
| Excel and SQL | Works, but Excel needs uploading or a Sheet in between | Native, strong |
| Tally | Via a scheduled export into Sheets or a database | Via Tally’s ODBC interface or scheduled exports; better for large ledgers |
| Data modelling | Light: blends and calculated fields | Heavy: relationships, DAX measures, Power Query clean-up |
| Refresh | On view, with caching per data source | 8 scheduled refreshes a day on Pro (shared capacity), up to 48 on Premium/PPU/Fabric |
| Learning curve | A few hours for a Sheets user | Days to weeks to learn DAX and modelling well |
| Mobile viewing | Browser, responsive layouts | Dedicated mobile app |
| Best for | Marketing, sales and ops dashboards on Google data | Finance, MIS and multi-source reporting at scale |
Prices change. Confirm Power BI on Microsoft’s India pricing page and Data Studio Pro on Google Cloud’s page before you budget.
How much does each cost for a 10-person team?
Take a 10-person team where 2 people build reports and 10 people view them. On free Data Studio the licence cost is ₹0; you pay only for whatever moves the data in (an Apps Script job, a connector subscription or a small database). On Power BI Pro all 10 viewers need a Pro licence: 10 × ₹1,165 = ₹11,650 a month, or about ₹1.4 lakh a year before GST, at the listed price.
That gap is why many SMEs start on Data Studio and move only specific finance or MIS reports to Power BI later. If your management already has Microsoft 365 E5 licences, check whether Power BI Pro is already included before buying it separately. For a full breakdown of build and maintenance costs, see our guide on Power BI dashboard cost in India.
What about Google Sheets and Tally data?
Google Sheets is where most Indian SMEs actually keep operating data: daily sales, collections, stock, leads. Data Studio reads a Sheet directly and is the path of least resistance. The catch is size: Google Sheets has a hard cap of 10 million cells per spreadsheet, and large Sheets get slow well before that. Once a sheet passes a few lakh rows, move the raw data into BigQuery or a Postgres database and keep only summaries in Sheets.
Tally is the other big source. Neither tool has a one-click Tally connector built by Microsoft or Google. The common routes are a scheduled export from TallyPrime (Excel or XML) into a shared folder, Tally’s ODBC interface read by Power BI Desktop through a gateway, or a third-party Tally sync tool that pushes ledgers into Sheets or a database. Power BI handles large ledgers and complex voucher joins better; Data Studio is fine if someone summarises the Tally data first.
When to pick which
Choose Looker Studio / Data Studio if
- Your data is mostly in Google Sheets, GA4, Google Ads, Search Console or BigQuery.
- Many people need to view the dashboard, including franchisees, clinic managers or agency clients, and you do not want to buy a seat for each.
- You want a working dashboard this week, built by someone who already knows Sheets.
- Reports are operational: daily sales by branch, leads by source, ad spend vs bookings.
Choose Power BI if
- Your finance team works in Excel and wants MIS with drill-downs, YoY and budget-vs-actual measures.
- You join several large sources: Tally, an ERP, a CRM, a SQL database.
- You need row-level security so each branch head sees only their branch, with audit trails.
- You already pay for Microsoft 365 and your IT team prefers the Microsoft stack.
Checklist before you build either dashboard
- Write down the 5 to 10 numbers the owner checks every day. Build those first, nothing else.
- Pick one source of truth for each number (Tally for revenue, CRM for leads) and agree on definitions.
- Automate the data feed before designing charts. A pretty dashboard on a manual export dies in a month.
- Decide who sees what. Branch-level access is easy in Power BI and needs separate data sources or filters in Data Studio.
- Set a refresh time that matches decisions, for example 8 AM daily for yesterday’s numbers.
- Add a ‘data last updated’ timestamp on every page so nobody acts on stale numbers.
- Keep the dashboard and data in your company’s own Google or Microsoft account, not a freelancer’s.
Can you use both together?
Yes, and many growing companies do. A common split is Data Studio for marketing and operations dashboards that many people view (branch managers, franchise partners, agency clients) and Power BI for the finance MIS that five people in the head office use. Both can read the same underlying database or BigQuery tables, so the numbers match as long as the metric definitions live in the data layer and not inside each tool.
The rule that keeps a two-tool setup sane: calculate metrics once, upstream, in SQL views or a clean summary sheet. If ‘net revenue’ is calculated separately in a Data Studio field and a Power BI DAX measure, the two will drift within a month and people will stop trusting both.
Common mistakes we see
The most common failure is building a 15-page dashboard nobody opens. Owners want one screen with the numbers that changed. The second is sharing Power BI reports with people who have free licences and discovering they cannot view them. The third is connecting Data Studio directly to a huge, formula-heavy Sheet, which makes every page load slowly. Fix these by keeping dashboards short, budgeting licences for viewers, and pre-aggregating data before it reaches the chart tool.
If you are also automating the reports that feed these dashboards, our guide on how to automate MIS reports covers the data pipeline step by step.
How Silvane can help
Silvane builds dashboards in whichever tool fits your data, in your own Google or Microsoft account, as part of the AI analytics team. The founder has run daily performance dashboards and reporting for a multi-city pet-care chain, so we start from the decisions the dashboard must support. A Starter build is from ₹50,000 with an optional run plan from ₹15,000 a month; licences are billed at cost and GST is extra. The ₹199 discovery call and AI audit (founding members, normally ₹15,000) tells you which tool to pick before you spend anything else. If the bigger problem is messy source data, see the AI data team.
Sources: Microsoft: Power BI pricing (India) · Microsoft Learn: Data refresh in Power BI · Google Cloud blog: Looker Studio is now Data Studio · Google Cloud: Data Studio