DATA & ANALYTICS | AI | CAREER TRANSITION

Helping Working Professionals Transition into Data Analytics

I help working professionals bridge the gap between learning analytics tools and becoming industry-ready Data Analytics professionals — through practical learning, real-world projects and 1:1 mentorship.

18+ Years in Analytics | PMP® Certified | Founder, QriusAI

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Deepti Nema

Data & Analytics Leader | PMP® | Founder, QriusAI

18+ Years

Analytics & IT Experience

PMP®

Certified Professional

Founder

QriusAI

Data & Analytics

Leadership & Mentorship

From Analytics Experience to Building QriusAI

Across 18+ years in IT and Analytics, I have worked across technology, data, projects and business problems.

STRATEGIC CAREER BREAK — AUGUST 2023

I took a strategic career break to explore something I had wanted to build for a long time — a more practical way for professionals to learn Data Analytics and transition into the field.

That journey led to QriusAI.

Today, I work with working professionals who want to move into Data Analytics, helping them understand not only the tools, but how analytics is actually applied in real-world business situations.

My focus is simple: move from learning tools to building real analytics capability.

What I Do

Career Transition

Transition into Data Analytics

Helping working professionals move from their current careers into Data Analytics with a structured, practical and industry-oriented approach.

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1:1 Mentorship

Learn by Building

Personalized guidance across analytics skills, real-world projects, business understanding, portfolio development and career positioning.

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Analytics Perspective

Data, BI & AI

Practical insights on Data Analytics, Power BI, Microsoft Fabric, AI, business intelligence and the changing analytics landscape.

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My Approach

Because learning tools is not the same as becoming an analytics professional.

UNDERSTAND

Understand the business problem, context and objective.

ANALYSE

Work with data and identify meaningful patterns and insights.

BUILD

Create practical analytics solutions and real-world projects.

COMMUNICATE

Turn analysis into clear business stories and decisions.

POSITION

Build the portfolio, professional profile and confidence needed for the next opportunity.

UNDERSTAND → ANALYSE → BUILD → COMMUNICATE → POSITION

You don't need another tutorial. You need the right approach to turn knowledge into capability.

Data Analytics careers are not built by collecting tools and certificates alone. They are built by understanding business problems, working with real data, building practical solutions, communicating insights and positioning yourself effectively.

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Who I Help

Working Professionals

Professionals looking to transition from their existing careers into Data Analytics.

Professionals Upskilling

People already working with data who want stronger BI, analytics, Python, SQL, Power BI or AI capabilities.

Career Transitioners

Professionals who have learned tools but need practical projects, portfolio development, positioning and interview readiness.

Data & Analytics Expertise

Analytics & BI

Power BI
Microsoft Fabric
Business Intelligence
Dashboard Design
Executive Reporting
KPI Design

Data

Excel
SQL
Python
Data Analysis
Data Modeling

AI

Generative AI
Prompt Engineering
AI-Assisted Analytics
AI & Analytics Transformation

Delivery

Project Management
Business Understanding
Stakeholder Management
Analytics Transformation
Data-Driven Decision Making

QriusAI

LEARN TO LEAD

QriusAI is the platform I built to help professionals develop practical Data Analytics capabilities and make meaningful career transitions.

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Practical Learning

Real-World Projects

1:1 Mentorship

Data & Analytics

AI & Modern Skills

Connect With Me on LinkedIn

I share practical perspectives on Data Analytics, AI, career transitions, BI, professional growth and the changing world of work.

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Learn With Me

Practical conversations and learning content around Data Analytics, Power BI, AI, career transitions and professional growth.

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Representative Case Studies

Sample Analytics Case Studies

Explore how I approach real-world analytics problems across different business scenarios. These are representative case studies designed to demonstrate my approach and the type of problems I can help solve.

CASE STUDY 01

Sample Scenario

Resource Utilization & Workforce Analytics

Business Challenge: How can an organization gain better visibility into resource allocation, utilization and capacity?
Approach: Analyse resource-level data, utilization patterns, allocation, availability and relevant KPIs.
Potential Solution: Build a structured analytics view or dashboard that helps stakeholders understand utilization patterns and resource allocation.
Business Insight: Move from fragmented resource reporting toward clearer visibility for planning and decision-making.

CASE STUDY 02

Sample Scenario

Executive KPI & Performance Dashboard

Business Challenge: How can leadership get a consistent view of important business performance indicators without relying on fragmented manual reports?
Approach: Identify business-critical KPIs, consolidate relevant data and structure the analysis around leadership questions.
Potential Solution: Create an executive-focused BI dashboard that brings key performance indicators into one decision-oriented view.
Business Insight: The purpose of an executive dashboard is not to show more data — it is to help leaders see what requires attention.

CASE STUDY 03

Sample Scenario

Sales & Business Performance Analytics

Business Challenge: How can a business understand sales performance, trends, product or region contribution and areas requiring attention?
Approach: Analyse sales trends, segmentation, contribution, performance drivers and relevant business KPIs.
Potential Solution: Build an interactive analytics solution that enables stakeholders to explore performance across relevant dimensions.
Business Insight: Good analytics should move the conversation from "What happened?" to "Why did it happen?" and "What should we do next?"

Have a specific analytics challenge in your domain?
The examples above are representative scenarios. Your business problem may require a completely different analytical approach.

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These are representative sample scenarios intended to demonstrate analytical approach and capabilities. Specific solutions and outcomes vary by business context.

Thinking About Your Next Move in Data Analytics?

If you're a working professional trying to transition into Data Analytics or looking for a more practical way to build your analytics career, let's talk.

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