Frequently Asked Questions (FAQ) | Datta Sable
Answers to common questions about Business Intelligence services, Power BI optimization, SQL automation, and timelines.
Frequently Asked Questions
Answers to the most common questions about Business Intelligence consulting, Power BI and Tableau development, data automation, pricing, timelines, and what to expect when working with Datta Sable.
What Business Intelligence tools do you specialize in?
I specialize in the full Microsoft BI stack — Power BI, Power Query, DAX, SQL Server, and SSRS — as well as Tableau Desktop and Advanced Excel automation using VBA and Power Query. For data engineering tasks I work with Python (pandas, SQLAlchemy, Prefect) and for cloud deployments, Azure Data Factory and AWS S3.
Do you handle custom data automation projects?
Yes, automation is a core service. I build Python and SQL-based ETL pipelines that replace manual data exports, scheduled email report generation using SMTP automation, Excel-to-dashboard pipelines with Power Query, and API integrations to pull live data from external platforms.
Can you optimize existing slow Power BI reports?
Absolutely. Slow Power BI reports are almost always caused by inefficient DAX measures that calculate at the row-level instead of the filter context, a star-schema data model that hasn't been properly normalized, or DirectQuery connections pulling from unindexed tables.
Do you provide MIS reporting services for Finance and Operations?
Yes, MIS reporting is one of my primary specializations. Over 10 years I have built automated MIS dashboards for banking (NPA tracking, collection efficiency, portfolio risk), telecom (churn analysis, revenue per circle), and manufacturing.
When Does a Business Intelligence Consultant Add Real Value?
Most organizations reach the same inflection point eventually: the Excel files that once managed the business are now too large to open, too slow to refresh, and too fragile to share. Analysts spend more time fixing broken formulas and consolidating weekly exports than they do actually analyzing data. This is the moment a Business Intelligence consultant becomes not just useful but essential.
A BI consultant does not just build dashboards — they design the data architecture that makes those dashboards reliable. This means auditing your existing data sources for quality and consistency, designing a data model that enables fast queries across millions of rows, and building the automated refresh pipeline that ensures your reports are always current without anyone pressing a button.
The Hidden Cost of Manual Reporting
Research consistently shows that analysts in data-heavy organizations spend 60-80% of their time on data preparation — collecting, cleaning, and consolidating data — and only 20-40% on actual analysis. This ratio is the inverse of what it should be. Every hour an analyst spends copying data between spreadsheets is an hour not spent identifying trends, anomalies, or opportunities that leadership needs to act on. The compounding cost of delayed insight is almost always larger than the one-time cost of building a proper BI infrastructure.
Power BI vs Tableau: Choosing the Right Platform
The most common question organizations face when starting a BI project is which tool to use. Power BI is the right choice if your organization is already in the Microsoft ecosystem — you use Azure, Office 365, SharePoint, or SQL Server. Its licensing model (Power BI Pro at approximately USD 10/user/month) is economical for large teams, and its native integration with Excel makes adoption easier. Tableau is the right choice when your data visualization requirements are complex — custom chart types, advanced spatial analysis, or pixel-perfect executive dashboards. Both tools are world-class; the right choice depends on your existing infrastructure, team skills, and budget.
What Separates a Good BI Project from a Great One
The difference between a BI project that gets used every day and one that gets abandoned within three months is almost never about the technology — it is about whether the dashboard answers questions that real decision-makers actually have. A great BI project starts with structured stakeholder interviews, not with data modeling. Understanding the specific decisions the CFO, operations manager, and sales director need to make every week dictates the KPIs, the data model, and the dashboard layout. When a dashboard is built backward from decision-making needs, adoption is natural. When it is built forward from available data, it becomes a technical artifact that nobody opens.
"The best BI system is the one your team uses every morning without being told to — because it answers the question they were going to ask anyway." — Datta Sable