AI & Technology Consulting
Data Engineering & Analytics
Clean, connected data pipelines that AI can trust.
What is Data Engineering & Analytics?
Data engineering is the work of collecting, cleaning and connecting data from many sources into pipelines, warehouses and dashboards, so that reporting and AI can rely on one accurate source of truth.
Overview
What Data Engineering & Analytics can do for you
AI is only as good as its data. We build the pipelines, warehouses and dashboards that turn scattered spreadsheets and systems into one reliable source of truth.
Outcomes you can expect
What we deliver
Our Data Engineering & Analytics services
Automated ETL/ELT from your apps, ERPs and M-Pesa.
A central, well-modelled store for analytics and AI.
Live KPIs in Power BI, Looker Studio or Metabase.
Checks and alerts that catch bad data early.
Use cases
Where it makes a difference
Popular ways our clients use Data Engineering & Analytics.
- Sales and finance reporting
- Customer 360 views
- Donor and programme reporting
- Demand forecasting
Process
How we deliver
- 1 Discover Free consultation: your goals, systems and quick wins.
- 2 Assess Readiness review of data, systems and skills.
- 3 Design Roadmap and solution blueprint with ROI.
- 4 Build PoC → MVP → production, with weekly demos.
- 5 Launch Rollout, training and change support.
- 6 Optimise Monitor, improve and scale what works.
Technology
Tools we use for Data Engineering & Analytics
PostgreSQL
BigQuery
Snowflakedbt
AirflowPower BIEngagement models
Pick how you want to start
Free
- Clear next steps
- Honest fit check
- No obligation
KES 7,500
- Found on Google and Maps
- WhatsApp ready to chat and sell
- Easy M-Pesa payments at your counter
KES 15,000
- One working automation live
- 1-hour AI training for your team
- Fixed price, no surprises
KES 30,000setup + KES 5,000/mo
- Answers FAQs 24/7, in English and Swahili
- Qualifies leads, books appointments
- Monthly support and tuning (Meta message fees at cost)
KES 50,000
- Fast, mobile-first website
- Found on Google search
- Cited in ChatGPT and Gemini answers
from KES 25,000
- Hands-on, on-site or live online
- Your documents and real tasks
- Playbook + certificate
from KES 60,000
- Readiness scorecard
- Ranked use cases + ROI
- 90-day roadmap
from KES 250,000
- Fixed scope & price
- Working product on your data
- Go / no-go report
from KES 150,000/mo
- Engineers + strategist
- Scale up or down
- Weekly reporting
FAQ
Data Engineering & Analytics: frequently asked questions
Straight answers about scope, cost, timelines and technology. Ask us anything else on WhatsApp.
What is Data Engineering & Analytics?
Data engineering is the work of collecting, cleaning and connecting data from many sources into pipelines, warehouses and dashboards, so that reporting and AI can rely on one accurate source of truth.
What does your Data Engineering & Analytics service include?
Our Data Engineering & Analytics service includes data pipelines, data warehouse, dashboards and data quality. Data pipelines: Automated ETL/ELT from your apps, ERPs and M-Pesa. Data warehouse: A central, well-modelled store for analytics and AI.
Who is Data Engineering & Analytics for?
Data Engineering & Analytics is a good fit for sales and finance reporting, customer 360 views, donor and programme reporting and demand forecasting. We work with SMEs, startups, enterprises, NGOs and public-sector teams.
What results can we expect from Data Engineering & Analytics?
Typical outcomes are one source of truth, reports in minutes, not days and AI-ready data foundations. We agree measurable success metrics before any build starts and report on them weekly.
How much does Data Engineering & Analytics cost?
Strategy sprint from KES 60,000 (≈ $465). Every engagement starts with a free 30-minute consultation, after which we send a fixed quote in Kenya shillings (or USD if you prefer). You can pay by M-Pesa, bank transfer or card, in instalments if that suits your cash flow, and we offer startup and NGO rates.
How long does Data Engineering & Analytics take?
Strategy sprint: 2–4 weeks. We share progress in weekly demos, so you see working results early rather than waiting for a big reveal at the end.
What technology do you use for Data Engineering & Analytics?
We commonly use PostgreSQL, BigQuery, Snowflake, dbt, Airflow and Power BI. We choose tools that fit your existing systems, budget and data-protection needs rather than forcing one stack.
We still run on Excel. Is that a problem?
Not at all. Most clients start there. We automate the spreadsheets first, then move to a warehouse when it makes sense.
Can you connect to M-Pesa statements?
Yes, via Daraja APIs or statement imports, depending on your setup.
Why choose Red Star Standard for Data Engineering & Analytics?
Red Star Standard is an AI consultancy and AI-driven software team. We pair AI strategy with the engineering to build it, agree measurable goals up front, deliver working results in weeks with weekly demos, and you own all code and data.
Related
You might also need
Related solutions
Often combined with Data Engineering & Analytics
Free · 30 minutes · No obligation
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