Common Questions
Frequently Asked Questions
Answers to common questions about data analytics, business intelligence, and how we help companies turn data into decisions.
What is a fractional CDO?
A fractional Chief Data Officer (CDO) is an experienced data executive who works with your company on a part-time or contract basis, providing strategic data leadership without the cost of a full-time executive hire. A fractional CDO typically costs 50-70% less than a full-time CDO while delivering the same strategic value: data strategy development, analytics roadmaps, team mentoring, and ensuring your data investments drive business results.
How much does data analytics consulting cost?
Data analytics consulting costs vary based on scope and engagement model. Project-based work typically ranges from $15,000-$100,000+ depending on complexity. Retainer or subscription models (like Sisu Analytics offers) range from $5,000-$25,000/month for ongoing support. Factors affecting cost include: data complexity, number of data sources, dashboard/report requirements, and whether you need strategic leadership or just technical implementation.
What is Microsoft Fabric?
Microsoft Fabric is an all-in-one analytics platform that unifies data engineering, data science, real-time analytics, and business intelligence into a single SaaS solution. It includes OneLake (a unified data lake), Data Factory for ETL, Synapse for data warehousing, and Power BI for visualization. Fabric simplifies the analytics stack by eliminating the need to stitch together multiple tools, and its pay-as-you-go model makes enterprise-grade analytics accessible to mid-market companies.
Power BI vs Tableau: which is better?
Power BI is generally better for organizations already using Microsoft products (Excel, Azure, Teams, SharePoint) due to seamless integration and lower cost ($10-20/user/month vs Tableau's $35-70/user/month). Tableau excels in complex visualizations and has a slight edge for data exploration. For most mid-market companies, Power BI offers the best value with its Microsoft 365 integration, natural language Q&A features, and embedded analytics capabilities.
What is ETL vs ELT?
ETL (Extract, Transform, Load) transforms data before loading it into the destination, while ELT (Extract, Load, Transform) loads raw data first and transforms it in the destination. ELT has become the modern standard because cloud data warehouses (Snowflake, Databricks, Microsoft Fabric) have massive compute power, making in-warehouse transformation faster and more flexible. ELT also preserves raw data for future use cases you haven't thought of yet.
How do I build a data warehouse?
Building a data warehouse involves: 1) Identifying key business questions and metrics, 2) Inventorying data sources (ERPs, CRMs, spreadsheets), 3) Choosing a platform (Microsoft Fabric, Snowflake, BigQuery), 4) Designing the data model (dimensional modeling with facts and dimensions), 5) Building ETL/ELT pipelines to load data, 6) Implementing data quality checks, and 7) Creating dashboards and reports. A typical mid-market data warehouse project takes 2-4 months and costs $30,000-$150,000.
What is data governance?
Data governance is the framework of policies, processes, and standards that ensure data is accurate, secure, and used appropriately across an organization. Key components include: data quality standards, access controls and security, data lineage documentation, metadata management, and compliance with regulations (GDPR, CCPA). Good data governance answers "Can I trust this number?" and prevents the spreadsheet chaos where every department has different figures.
How do I measure analytics ROI?
Measure analytics ROI through: 1) Time savings (hours saved on manual reporting × hourly cost), 2) Revenue impact (decisions enabled by data that drove revenue), 3) Cost avoidance (problems caught early, inventory optimization), 4) Speed to insight (time from question to answer), and 5) User adoption (% of employees using dashboards regularly). A well-implemented analytics program typically shows 5-10x ROI within the first year through better decision-making and operational efficiency.
What industries does Sisu Analytics serve?
Sisu Analytics specializes in three industries: 1) Multi-family property management (Yardi, RealPage, CoStar integrations), 2) SaaS and subscription businesses (ARR, MRR, churn, LTV/CAC metrics), and 3) Agriculture and AgTech (precision farming, yield analytics, supply chain). Our proven frameworks adapt to any industry, but these verticals benefit from our deep domain expertise and pre-built data models.
What does "Sisu" mean?
Sisu (pronounced "see-soo") is a Finnish concept that translates roughly to extraordinary determination, courage, and resilience in the face of adversity. It's the grit to push through when things get hard. We chose this name because transforming messy, disconnected data into actionable insights requires exactly this kind of relentless determination. We bring sisu to every engagement.
Still Have Questions?
Let's Talk About Your Data
Every company's data challenges are unique. Schedule a free consultation to discuss your specific situation.
Schedule a Call