Snipher Marube Abel

15/03/2026

Building something exciting today…
Spent most of the day deep in development working on AnalyticsMeta, the analytics platform I’m building to make data insights easier and more accessible for teams.
One thing I keep seeing across organizations is this: people have data, but they struggle to turn it into insights quickly. That’s the problem I’m trying to solve.

Here’s some progress from today:
🔌 Real-time dashboards
We implemented WebSocket infrastructure so dashboards update live without refreshing the page. This also opens the door for multiple users collaborating in real time.

📊 Smarter data visualization
The system can now analyze a user-defined schema (for example a sales pipeline with deal value, status, stage, etc.) and automatically generate relevant charts and metrics.

🤖 Preparing for AI insights
We’re laying the foundation for AI-powered analytics. Soon the platform will be able to surface insights such as:
- Changes in performance trends
- Revenue projections
- Deals or opportunities that may be at risk

🎨 A clean, production-ready dashboard
We also improved the user experience with:
- Drag-and-drop dashboard layouts
- Real-time collaboration indicators
- Responsive charts powered by Plotly
- Better error handling and performance

Tech stack behind it
- Python + Django
- Django Channels for WebSockets
- Redis for real-time messaging
- Plotly for interactive visualizations

The bigger vision
The goal with hashtag is simple:
Make it possible for teams to create data tables, dashboards, and insights without needing data engineers or complex BI tools.
If we do this right, organizations will spend less time preparing data and more time making decisions.

Next step: integrating predictive analytics and cross-dataset insights so the platform can move from reporting data to explaining what it means.

Building in public is always fun.
Would love to hear from others building in data, AI, or analytics platforms.
hashtag hashtag hashtag hashtag hashtag hashtag hashtag hashtag hashtag

10/03/2026

Your business data is talking. Are you listening? 👂
Every day, SMEs generate valuable data:
🛒 Sales transactions
💰 Expense records
📦 Inventory movements
👥 Customer interactions

But here's the harsh reality: most of this data sits untouched in spreadsheets, never revealing the insights that could transform a business.
That's exactly why I'm building Business Sight Technologies.
For the past 6months, I've been working tirelessly to create something I genuinely believe SMEs need—a way to finally make sense of their numbers without the headache.

✨ What we're building:
📊 Create your tables – define what matters to YOUR business (not what some software thinks should matter)
📤 Add your records – manual entry, CSV upload, or API (however you work best)
🤖 Get instant insights – our engine automatically generates dashboards, charts, and KPIs based on YOUR data structure
👥 Go deeper – when you're ready, our financial consultants will help interpret findings and create actionable strategies

Where we are right now:
I'm deep in the trenches building version 1.0. The core functionality is taking shape—users can create tables, add records, and we're perfecting the automatic visualization engine that makes sense of it all.

Why I'm sharing this now:
Because the best products are built with the people who'll use them.
I'm looking for 10 forward-thinking SME owners who'd be interested in:
✅ Getting early access before the public launch
✅ Shaping the product with your feedback
✅ A FREE onboarding and data health check when we launch
✅ A lifetime discount as a founding user
No polished sales pitch. No pressure. Just a genuine invitation to build something useful together.

If this resonates with you—or you know someone who's constantly fighting with spreadsheets—I'd love to connect.
Comment "DATA" below or DM me, and I'll add you to my insider list. 🙏
hashtag hashtag hashtag hashtag hashtag hashtag

08/03/2026

The Importance of Data Pipelines in Monitoring & Evaluation (M&E)

Monitoring and Evaluation (M&E) is only as strong as the data behind it. Many organizations invest heavily in programs, projects, and interventions, yet struggle to clearly measure impact. The core problem is often not the absence of data — it is the absence of structured data pipelines.

A data pipeline is the system that collects, processes, transforms, and delivers data from different sources into a format that can be analyzed and used for decision-making.

In the context of M&E, this becomes critical.

First, data pipelines ensure consistency and reliability of data. When program data comes from multiple sources—field surveys, mobile data collection tools, spreadsheets, CRMs, or operational systems—it can easily become fragmented. A well-designed pipeline standardizes and validates this data before it reaches dashboards or reports. This significantly reduces human errors and inconsistencies.

Second, they enable real-time or near real-time monitoring. Traditional M&E workflows often rely on periodic manual reporting. By the time reports are compiled, the opportunity to respond to issues may already be lost. Automated pipelines allow organizations to continuously ingest and process data, enabling teams to detect trends, identify bottlenecks, and intervene earlier.

Third, data pipelines improve transparency and accountability. When data flows automatically into centralized systems such as data warehouses or analytics platforms, stakeholders—from program managers to donors—can access reliable insights. This builds trust and ensures decisions are backed by evidence.

Fourth, they unlock advanced analytics and impact measurement. Once data is structured and centralized, organizations can move beyond descriptive reports to deeper analysis such as trend forecasting, performance benchmarking, and impact attribution.

Finally, data pipelines create scalability. As organizations grow, so does the volume and complexity of their data. Without automation, M&E teams quickly become overwhelmed by manual data cleaning and consolidation tasks. Pipelines allow systems to scale without increasing operational overhead.

For organizations working in development, humanitarian programs, research, or social impact initiatives, building strong data infrastructure is no longer optional.

Effective Monitoring and Evaluation starts with effective data engineering.

When data flows seamlessly from collection to insight, organizations move from reporting activities to demonstrating real impact.

20/12/2025

Good morning my people

18/12/2025

18/12/2025

18/12/2025

Are you in tech?

06/12/2025

🔁 Multi-Layer Flow
- Ingestion Layer – Handles high-throughput data intake with built-in buffering and validation.
- Processing Core – Stateless services with parallel ex*****on paths for real-time transformation.
- Storage & State – Tiered persistence (hot/warm/cold) with intelligent caching and consistency guarantees.
- Orchestration & Observability – Centralized workflow management, health checks, and distributed tracing.

🧠 Key Design Principles
- Decoupled & Async – Event-driven communication between modules.
- Resilient & Retry-Ready – Failures are isolated and replayable.
- Observable by Design – Every component emits metrics, logs, and traces.
- Configurable & Environment-Aware – Dynamic routing and feature flags.

⚙️ Tech Highlights
- Microservices over monoliths
- Message queues for async workflows
- API gateways with rate limiting & auth
- Containerized deployments + service mesh for inter-service communication

This architecture is built to evolve—ready for new features, regulatory changes, and unpredictable load.

💬 What would you add or adjust? Have you worked with a similar setup? Let’s discuss in the comments!

06/12/2025

First make the change easy (warning: this might be hard), then make the easy change.

22/11/2025

E-commerce is booming in rural Kenya, outpacing urban growth according to Jumia's latest report! The digital economy is reaching every corner of the country.