Data Analytics & Business Intelligence

About this Gig

I provide end-to-end Data Analytics and Business Intelligence consulting services that help organizations turn complex data into clear, actionable business insights. My work spans data strategy and architecture, advanced analytics, and enterprise BI modernization, enabling leaders to make faster, more confident, data-driven decisions. I specialize in designing and delivering scalable cloud data platforms, building executive dashboards and performance reporting, and leading analytics transformations across the full data lifecycle—from data engineering and governance to predictive and prescriptive analytics. My focus is not just on technology, but on aligning analytics with business strategy to drive measurable outcomes in performance, efficiency, and growth. Through strong data governance and quality frameworks, I ensure that analytics solutions are trusted, secure, and sustainable. Ultimately, I help organizations move from fragmented data to decision intelligence, turning data into lasting business value.

Requirements

1. Business Objectives & Priorities • Key business goals you want analytics to support • Strategic initiatives or decisions you are trying to improve • Success criteria and expected business outcomes This helps align the analytics work directly with business value. 2. Stakeholders & Governance • Primary business sponsor and technical owners • Key users of reports and dashboards • Decision-makers and escalation points • Any existing data governance or approval processes Clear ownership ensures fast decisions and smooth delivery. 3. Current Data Landscape • List of core data sources (ERP, CRM, finance, operations, etc.) • Overview of current data platforms, warehouses, or lakes • Existing dashboards, reports, or analytics tools in use • Known data quality or integration issues This allows me to assess readiness and design the right architecture. 4. Access & Technical Environment • Read-only access to relevant data systems (where possible) • Documentation of data models, schemas, and pipelines • Cloud platform details (Azure, AWS, GCP, on-prem) • Security, compliance, and access requirements This enables accurate scoping and hands-on delivery. 5. Reporting & Analytics Requirements • Key KPIs and performance metrics • Priority dashboards and reports • Frequency of reporting (real-time, daily, monthly, executive) • Target user groups and usage scenarios This drives user-focused, adoption-ready solutions. 6. Maturity & Roadmap Context • Current analytics maturity level • Past or ongoing analytics initiatives • Short-term quick wins vs. long-term transformation goals • Budget, timeline, and delivery constraints This helps balance immediate value with sustainable architecture.

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