Freelancers using Google BigQuery in IndiaFreelancers using Google BigQuery in India
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Prem Patel's avatar
Prem Patel
proIndia
Make.com Level 5 & Zapier Expert: AI and Ops Automation
10
Followers
Make.com Level 5 & Zapier Expert: AI and Ops Automation
Cover image for Does someone on your team
Does someone on your team lose a day or two building the sales report every week or month? That was the starting point at Mokobara, the premium travel brand. Pulling sales across all their stores, checking returns, reconciling the numbers and emailing each manager took 1 to 2 days every cycle, with 8+ hours of that spent just reconciling. I built them an automation on Make.com (http://Make.com) a few months ago. It has run on its own ever since, weekly and monthly: Make pulls every sales record from BigQuery, 100K to 250K per cycle. That is too many for one request, so it reads them page by page and stitches them back together. It calculates the numbers the team actually uses: net sales per store after returns and discounts, return rates and the change against the last period. It builds a CSV with the full breakdown and a short email summary you can read in 60 seconds. It reads a Google Sheet of store representatives and emails every one of them the report for their own store. The result: the reporting problem is gone. The report went from 1 to 2 days of manual work to fully automatic, and the 8+ hours of reconciliation dropped to zero. Two things I would do the same way again: Calculate "net sales" in the automation, not in the warehouse. The business rule for what counts as a net sale is not what the raw data stores. Send people their slice, not the whole report. One report for everyone gets skimmed by everyone. The figures in the image are placeholders, the real ones stay with the client. What report is your team still building by hand? Tell me where the data lives and I will tell you how I would automate it.
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Cover image for How do you automate a
How do you automate a daily sales report from BigQuery to Slack with Make.com, when the data is 250,000 rows and the reader is not an analyst? Six decisions make or break it. A direct-to-consumer brand's daily sales report took one to two days to compile, which meant Monday's numbers arrived on Wednesday. A 7 AM Make.com scenario now pages the data out of BigQuery, computes the KPIs and posts a plain-English summary to Slack and email before anyone opens a laptop. The six decisions: 1. Page, do not pull. A day can be up to 250,000 rows. The scenario pages through BigQuery in chunks and aggregates as it goes, so no single step holds the whole table. 2. Compute the KPIs in the scenario, not in the prompt. Revenue, orders, average order value, top products and day-on-day change are arithmetic. The model only writes the sentences. 3. Give the model numbers, never the rows. A short structured summary goes to OpenAI with a fixed template; the output is two paragraphs a founder reads in thirty seconds. 4. Check before you post. If a KPI is null, if the row count is far below the trailing average, if a query failed, the scenario alerts the owner instead of posting a confident wrong report. 5. Post where people already look. Slack channel at 7 AM plus an email copy for the people not in Slack. No dashboard to remember to open. 6. Keep a paper trail. Every run logs the query window, row count, KPIs and the text it posted, so a number can be traced back a month later. The diagram shows the run: schedule, paged query, KPI step, summary, checks, Slack and email. The full case study is on my profile. The same scenario shape works with Shopify, Stripe, a CRM or a Sheet as the source. Prem Patel, Nex Automations. Make.com Level 5 certified, official Make partner, Zapier Certified Expert.
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Cover image for BigQuery to Slack daily sales reports on Make.com, D2C brand
BigQuery to Slack daily sales reports on Make.com, D2C brand
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Cover image for Is your Contra discovery score
Is your Contra discovery score stuck? Mine went from top 45% to top 20% in 13 days, and posting more is not what moved it. And i need real Project On Contra😅 I log my score on every tag with a small script that reads all 48 options on the discovery page, so this is what actually changed between 27 August and 9 September 2026, and what did not. What moved it: Case studies. From 0 passing Contra's quality check to 15. Contra's checklist is short: a custom cover, a clear descriptive title, an engaging description, in-depth content and real media. My first two projects failed it, one on the description and one on the media. Services. From 1 passing service to 9, each with its own cover, a descriptive title, a rate and a real summary. Every tag a service carries gets the lift, so tag the tools you actually used. Profile quality, 66% to 100% after the profile rewrite. Replying to the first inquiry quickly. Response time was blank until then. It now reads 2 hours. The result: Overall top 45% to top 20%. Automation Engineer top 25% to top 10%. Make top 35% to top 20%. What did not move it: the four days after. From 9 to 13 September every tag gained exactly 1 point. Nothing new on the profile, nothing moves. And the three biggest levers on my board are still at zero: earnings, reviews and verified projects. All three come from the same move, one paid project routed through Contra, so that is where my next week goes. One thing if you compare yourself with others: Contra's point scale changed between my runs, so compare your rank band (top X%) rather than the raw points. What moved yours? If yours is stuck, reply with your score and the tag, and I will tell you which lever I would pull first.
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Google BigQuery(3)
Varun Sethi's avatar
Varun Sethi
proChandigarh, India
Full-Stack Developer | React, Next.js, Node.js & Python
New to Contra
Full-Stack Developer | React, Next.js, Node.js & Python
Cover image for I designed and built Distill
I designed and built Distill IQ, a full-stack retail pricing intelligence platform for a US-based liquor business. The application processes and presents large-scale pricing data through interactive product surveys, competitor comparison analytics, raw data exploration, and user/access management. I worked across the React frontend, Python backend, APIs, BigQuery data layer, business logic, and UI components to build the platform from the ground up. Key features: Pricing Survey: 5,200+ SKUs, 110+ brands, search and advanced filtering Competitor Analytics: Compare products across markets with average, median, mode, price ranges, and price gaps Market Analytics: Interactive price distribution, historical trends, and competitor comparison Raw Data Explorer: BigQuery-backed data exploration with filtering, pagination, and export User Management: User accounts, roles, permissions, market access, and catalog management Reusable UI: Tables, filters, cards, charts, forms, and responsive components
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Cover image for Manufacturing Quality & Operations Platform I
Manufacturing Quality & Operations Platform I designed and developed the frontend for a production-grade manufacturing quality and operations platform used within a multibillion-dollar global consumer goods enterprise. The application brings quality workflows, production reporting, SKU management, plant-level analytics, and role-based operations into a single platform. I worked across the Next.js application architecture, UI/UX implementation, API integrations, authentication, state management, reporting workflows, and reusable component system. Key areas - Operations & Reporting: Adoption, SKU Plant Summary, Plan vs Actual, PCP Tracker, PCRO and CRQS reports - Quality Workflows: Product/SKU management, barcode scanning, product -verification and multi-step SKU creation - LQA Operations: Pending SKU workflows, employee/site selection, product details, barcode capture and validation - Shift Supervisor: Employee selection and role-specific workflows - Analytics: KPI cards, donut/bar charts, trends, filters and deep-dive analytics - Admin: Site management, user profile, role-based access and protected routes - Reusable UI: Tables, charts, cards, modals, forms, tabs, filters, dropdowns and navigation components
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Cover image for Hi, I designed and developed
Hi, I designed and developed Quality Station, a web application for managing and analysing manufacturing quality checks. The product brings together quality dashboards, product management, inspection sessions, AI-based analysis, defect detection, user management, and activity tracking into a single interface. The UI was designed in Figma and implemented as a functional React/Next.js application, with a reusable component system, responsive layouts, interactive charts, data tables, filters, modals, forms, and multi-step workflows. Key areas I worked on include: - Analytics dashboards and quality monitoring - AI performance and defect analysis - Quality sessions with product/barcode verification - Weight, barcode, and OCR analysis - Live image and analysis views - Product management and configurations - User roles and access management - Activity tracking - Reusable tables, charts, forms, filters, and UI components
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Cover image for AI Data Assistant Inside Tableau I
AI Data Assistant Inside Tableau I built an AI-powered chatbot for Tableau that allows users to interact with their existing dashboards and data through natural-language questions. Instead of manually navigating through multiple Tableau workbooks to find a specific metric or insight, users can ask the assistant what they need and receive relevant information from the available Tableau data and dashboards. The solution adds a conversational AI layer directly to the existing BI workflow, helping users explore their data and find the right dashboard or report without changing how their Tableau environment is structured.
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Google BigQuery(1)
Gourav Kondadadi's avatar
Gourav Kondadadi
Bengaluru, India
Growth Manager with 8+ years experience of AI in Growth
New to Contra
Growth Manager with 8+ years experience of AI in Growth
Cover image for Enterprise Marketing Analytics & Attribution
Enterprise Marketing Analytics & Attribution — West Pharmaceutical Services Built analytics and measurement systems connecting digital marketing, customer behavior, CRM, advertising, and commercial outcomes for a global enterprise. Worked across GA4, GTM, BigQuery, SQL, Python, Power BI, advertising platforms, customer identity resolution, attribution, and executive reporting. Programs contributed to major improvements in digital revenue, sales efficiency, onboarding performance, retention economics, and visibility into marketing ROI. Skills: GA4, GTM, BigQuery, SQL, Power BI, Attribution, Marketing Analytics, CRM
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Cover image for Zero-to-20K User Growth — AI
Zero-to-20K User Growth — AI Product Helped grow an AI product from zero to approximately 20,000 users without relying on paid acquisition. The work combined positioning, organic distribution, product-led growth, experimentation, audience development, analytics, and rapid iteration to identify repeatable acquisition loops. Skills: Product-Led Growth, Organic Growth, AI Marketing, Growth Experiments, Analytics
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Cover image for Building the Growth Engine for
Building the Growth Engine for MinionArts Built and operated MinionArts' early growth and distribution engine across organic acquisition, founder-led sales, partnerships, outbound, creators, content, and performance marketing. The work included ICP development, messaging, campaign experimentation, lead generation, sales outreach, analytics, attribution, and converting product capabilities into commercially relevant use cases for brands and studios. Skills: Growth Strategy, Demand Generation, GTM, Marketing Automation, Founder-Led Sales
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Cover image for MinionArts — AI-Native Creative Production
MinionArts — AI-Native Creative Production Platform Co-building MinionArts, an AI-native creative production platform for brands, agencies, and studios producing high-volume visual content. Worked across GTM, positioning, sales, partnerships, distribution, pricing, product strategy, and customer acquisition while helping develop workflows spanning script, storyboard, characters, scenes, voice, video generation, and final creative output. MinionArts grew to thousands of users through largely organic and founder-led distribution. Skills: AI Strategy, GTM, Product Marketing, Growth, B2B Sales, Generative AI
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Google BigQuery(1)
Smita S's avatar
Smita S
Pune, India
Senior Data Analyst | Business Intelligence Consultant
11
Followers
Senior Data Analyst | Business Intelligence Consultant
Cover image for MRR & Churn Analysis Dashboard for SaaS Retention and Growth
MRR & Churn Analysis Dashboard for SaaS Retention and Growth
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Cover image for Power BI Templates for Self-Service Reporting
Power BI Templates for Self-Service Reporting
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Cover image for Inventory Optimization with ABC-XYZ Segmentation
Inventory Optimization with ABC-XYZ Segmentation
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Google BigQuery(1)
Vikas Kashyap's avatar
Vikas Kashyap
Delhi, India
Data visualization engineer, Data Analyst, BI Expert
13
Followers
Data visualization engineer, Data Analyst, BI Expert
Cover image for Ecommerce Analytics Dashboard in Looker Studio
Ecommerce Analytics Dashboard in Looker Studio
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Cover image for Executive Summary Dashboard for Google Merchandise Store
Executive Summary Dashboard for Google Merchandise Store
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Cover image for National Accident Statistics Dashboard in Google Looker Stud...
National Accident Statistics Dashboard in Google Looker Studio: I built an interactive Looker Studio dashboard using Google Sheets as the data source to visualize national accident statistics. The report analyzes accidents by region, time, severity, and demographics. A scheduled data re:fresh every 15 minutes keeps the dashboard updated in real time. As a Data Visualization Expert, I combined automation and design to deliver a clean, insightful, and dynamic Looker Studio dashboard for data-driven decision-making. 🎉 💯 🎉
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Cover image for Power BI Dashboard for Full-Body Alignment Assessment
Power BI Dashboard for Full-Body Alignment Assessment
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Google BigQuery(1)
Aadi Kalra's avatar
Aadi Kalra
Sonipat, India
Product Associate
New to Contra
Product Associate
Cover image for B2C Marketing Case Competition
B2C Marketing Case Competition
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Cover image for Hi everyone, so its my day
Hi everyone, so its my day 1 here on contra, who am I? just a normie 19 year old in his first year of CS major trying to figure things out, so I have won around 7 Hackathons and few Product competitions? including wins at various IITs and IIMs and those wins made me realize one thing for sure- "I AM NOT MADE FOR CLASSIC 9 TO 5" and what made me realize that? I love interacting and building things together , i don't like those classy cubicle jobs, i learn by interacting and I am trying to discover what i want, being very honest i really am confused about what I am gonna do but one thing that I am sure about is I am gonna do something and figure things out by trying every shit I can and getting my hands dirty , at the same point I want to connect with you all and learn as much as i can from you guys(and obv always open to build something together :) ) so if you wanna connect, am just a DM away , will keep posting on daily basis ,trying to get some interactiveness here as well😔✋🏻. will see you all tomorrow after completing another day of productivity :) .
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Cover image for Enhancing LinkedIn's Job Experience
Enhancing LinkedIn's Job Experience
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Cover image for Best Freshers Team Win at CONSTRUCT
Best Freshers Team Win at CONSTRUCT
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Google BigQuery(1)
Devyansh Rajput's avatar
Devyansh Rajput
India
Data Analyst | SQL, PowerBI, Tableau, Python
Data Analyst | SQL, PowerBI, Tableau, Python
Cover image for NYC Taxi & Limousine Commission Data Analytics
NYC Taxi & Limousine Commission Data Analytics
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Cover image for Sales Insights FMCG Data Analysis
Sales Insights FMCG Data Analysis
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Cover image for Space Missions Analysis : 19757 - 2022
Space Missions Analysis : 19757 - 2022
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Google BigQuery(1)