Data Analytics for SMEs

Simple, affordable, and production-ready analytics that turn your data into decisions — without enterprise complexity or heavy licensing.

Showcase image

We help SMEs make sense of their data by connecting information across tools, cleaning it, and making it usable for real business decisions. Our focus is practical impact, not complex infrastructure

What we support at Data

We help SMEs make sense of their data by connecting information across tools, cleaning it, and making it usable for real business decisions. Our focus is practical impact, not complex infrastructure.

We support you across:

Data integration and unification

  • Connect CRM, ticketing, bookings, payments, and conversation data (voice, chat, WhatsApp)
     
  • Create a single source of truth for your business metrics
     
  • Normalize and clean messy real-world data
     

Business analytics and reporting

  • Define clear KPIs that matter to your business
     
  • Build role-based dashboards for founders, operations, and CX teams
     
  • Provide real-time and periodic reporting
     

Predictive intelligence

  • Lead conversion prediction
     
  • Churn risk identification
     
  • Ticket escalation forecasting
     
  • Demand and workload prediction
     
  • Expected resolution time estimation
     

Actionable insights

  • Identify bottlenecks in customer journeys
     
  • Highlight automation ROI
     
  • Surface cost per conversation and efficiency gains
     
  • Recommend operational improvements
     

Technology Stack We Use

We intentionally avoid heavy, license-driven platforms like Databricks for SMEs. Instead, we use a modern, lightweight, and cost-effective stack that is powerful yet easy to operate.

Data layer

  • Cloud data warehouses like BigQuery, Snowflake, or Redshift
     
  • Streaming ingestion where real-time data is needed
     
  • Secure data connectors to your existing systems
     

Processing and analytics

  • Python-based data pipelines for transformation and enrichment
     
  • NLP models for intent, sentiment, and pattern detection
     
  • Predictive models tailored to your business context
     

Visualization and insights

  • BI tools like Looker Studio, Power BI, or Tableau
     
  • Custom dashboards built for your roles and KPIs
     
  • Alerts and anomaly detection for proactive action
     

Integrations

  • Salesforce, HubSpot, Zoho CRM
     
  • Zendesk, Freshdesk, Jira
     
  • Calendly, Google Calendar, payment systems
     
  • WhatsApp, voice platforms, and internal tools
     

Security and governance

  • Data isolation per client
     
  • Role-based access control
     
  • Encryption in transit and at rest
     
  • Audit logs and retention policies
     

How It Works

  • 1

    Discover and Define your data landscape

    We begin by understanding both your business goals and the data you already generate. Most SMEs have valuable data spread across many tools, so we map everything clearly before designing analytics.

    We typically review

    • CRM, ticketing, bookings, and payments
       
    • Voice, chat, and WhatsApp data
       
    • Operational databases like PostgreSQL, MySQL, or MS SQL
       
    • Application logs and system metrics
       

    We also clarify what is stored in structured databases, what comes via APIs, what lives in spreadsheets, and what is real-time versus batch data.

    Step illustration
  • 2

    Connect and Clean using SQL, databases, and observability

    After mapping your data sources, we focus on building a reliable, transparent data foundation using industry-standard practices rather than black-box tools. We connect directly to your existing SQL databases such as PostgreSQL, MySQL, MS SQL, or cloud warehouses, and create clean, well-structured data layers using SQL and Python. Instead of fragmented tables spread across systems, we design a unified analytics model that brings consistency, clarity, and trust to your data.

    Alongside this, we add operational visibility so analytics goes beyond business reports. Using Prometheus, we capture real-time system metrics such as API latency, error rates, and usage spikes, and visualize them through intuitive Grafana dashboards. This allows us to correlate technical performance with business outcomes for example, understanding how slow APIs impact customer experience, resolution times, or conversions.

    By combining structured data engineering with observability, your analytics does not just tell you what happened in your business; it helps you understand why it happened and how to improve it.

    Step illustration
  • 3

    Visualize and Validate with the right tools

    On top of clean data and observability, we make insights easy to use.

    • Business dashboards in Looker Studio, Power BI, or Tableau
       
    • Real-time operational views in Grafana
       
    • SQL views powering both technical and business reporting
       
    • Ability to drill from KPIs down to raw data when needed
       
    Step illustration

Have something in mind?

Share your data sources, reports, or key business questions. We’ll design a production-ready analytics approach with clear timelines and a fast path to measurable results.

May We Know You?

We Dont Store Your Data

Error. Your form has not been submittedEmoji
This is what the server says:
There must be an @ at the beginning.
I will retry
Reply