Sukannia Suresh | Data Analyst Portfolio

ABOUT ME

From Banking Operations to Data Analytics

A unique intersection of operational rigor, business domain expertise, and advanced analytical problem-solving.

Bridging Real-World Business with Data

I have over six years of experience working in banking operations and application support at Australian New Zealand Bank (ANZ), where I managed business-critical workflows, SLA-driven incident resolution, access management, BRD documentation, and daily operational reporting.

As I worked closely with operational systems and reporting bottlenecks, I developed a passion for extracting deeper answers from raw numbers. I systematically elevated my technical toolkit in Excel, Power BI, Tableau, SQL, and Python to transform raw business data into clear, decision-ready intelligence.

Unlike purely theoretical analysts, my background equips me with genuine domain intuition: I understand SLA constraints, financial metrics, customer friction points, and stakeholder expectations.

Business Domain Intuition

SLA & Operational Excellence

Financial & Process Modeling

Decision-First Dashboarding

Core Analytical Stack

Power BI Tableau Advanced Excel SQL Python Pandas

SKILLS & COMPETENCIES

Tools & Technologies I Work With

A comprehensive toolkit spanning business intelligence, database querying, programming, and process management.

BI & Data Visualization

Building interactive, executive-ready dashboards with clear visual storytelling and KPI drill-downs.

Power BI Tableau Advanced Excel DAX Measures Calculated Fields Pivot Tables & Charts Power Query Interactive Slicers

SQL & Data Querying

Extracting, filtering, transforming, and summarizing complex multi-table relational datasets.

Joins (Inner, Left, Outer) GROUP BY & Aggregations CASE WHEN Logic Subqueries Window Functions Data Filtering Data Cleaning

Python & Scripting

Writing programmatic logic, manipulating structured data structures, and exploratory data analysis.

Python Programming Pandas Jupyter Notebook Anaconda Data Structures Conditional Logic Exploratory Analysis

Data Analytics & Modeling

Translating ambiguous business challenges into structured hypotheses and quantifiable insights.

Data Cleaning & Wrangling Trend & Attrition Analysis Financial Ratio Analysis Root Cause Diagnostics Working Capital Analysis CSAT & KPI Tracking

Business Domain & Operations

6+ years of front-line banking operations, SLA governance, and stakeholder alignment.

Banking Operations SLA Management ServiceNow Ticketing Access Administration BRD Documentation Audit & Compliance Stakeholder Reporting

Collaboration & Strategy

Communicating technical findings clearly to both business leaders and technical teams.

Executive Presentation Cross-functional Teaming Process Streamlining User SOPs & Guides Requirement Gathering Actionable Recommendations

FEATURED CASE STUDIES

High-Impact Analytics Projects

Real business questions solved through data modeling, interactive dashboards, and actionable recommendations.

Banking Customer Satisfaction Dashboard Screenshot

Microsoft Excel

Project Presentation Deck: Banking Customer Satisfaction

In-Site Deck Viewer

EXCEL ANALYTICS DECK

Case Study: Banking Customer Satisfaction & Backlog Optimization Slide 1 / 4

1. Executive Summary & Problem Statement

Analyzed 1,200 customer complaints to diagnose resolution bottlenecks, service quality variations, and root-cause drivers of customer dissatisfaction in retail banking.

1,200Complaints

783Resolved (65.3%)

417Pending Backlog

3.22/5Average CSAT

2. Complaint Type & Resolution Analysis

Fraud Investigation emerged as the single highest volume complaint category and exhibited the longest average resolution duration across all channels.

Fraud cases require multi-tier investigations, leading to elevated resolution cycle times.
Complaints were evenly distributed across Online, Mobile, Branch, and Phone channels.

3. Customer Satisfaction Diagnostics

While 5-star ratings formed the largest single bucket, the aggregate satisfaction score averaged 3.22 / 5.00, dragged down by protracted resolution delays.

Complaint volumes fluctuate seasonally without a fixed linear trend.
Communication frequency during investigations is the top driver of negative ratings.

4. Strategic Recommendations & Action Plan

Dedicated Fraud Fast-Track: Restructure fraud workflows to resolve routine inquiries 30% faster.
Backlog Reduction Sprint: Deploy targeted resources to clear the 417 pending/in-progress cases.
Proactive Updates: Introduce automated milestone SMS/Email alerts to uplift CSAT.

FEATURED PROJECT 01 Excel Analytics

Banking Customer Satisfaction Dashboard

Comprehensive analysis of 1,200 customer complaints to identify resolution gaps, complaint distribution patterns, customer satisfaction scores, and service resolution efficiency.

1,200 Complaints Analyzed

783 Resolved Cases (65.3%)

417 Pending / In-Progress

3.22 / 5 Overall Average CSAT

                      Critical Finding: Fraud Investigation had the highest complaint volume and longest resolution time, creating a major backlog bottleneck.
                    

                      Core Recommendation: Prioritize fraud investigation workflows, clear the 417-ticket pending queue, and implement automated customer status updates.
                    

Excel Pivot Tables Pivot Charts Advanced Formulas Dashboarding

Interactive View

HR Workforce and Performance Tableau Dashboard Screenshot

Tableau Desktop

Project Presentation Deck: HR Workforce & Performance

In-Site Deck Viewer

TABLEAU HR ANALYTICS DECK

Case Study: Workforce Composition, Attrition & Productivity Analysis Slide 1 / 4

1. Executive Summary & Workforce Scope

Evaluated 2,500 employee records to uncover workforce distribution, department-level attrition, attendance correlation, training effectiveness, and salary patterns.

2,500Employees

27.8%Sales Attrition

3.8 / 5Avg Performance

4Salary Bands

2. Department Attrition Disparities

Sales department suffered the highest attrition rate at 27.8%, while IT demonstrated the lowest attrition. The workforce remained balanced across full-time and contract cohorts.

Identified where turnover concentrates to direct qualitative HR interventions.
IT maintains highest department headcount with stable retention rates.

3. Attendance & Training vs Performance

Scatter plot analysis revealed a positive statistical association between high attendance percentages and superior performance appraisal scores.

Evaluated whether training hours translate to higher performance ratings.
Roughly 50% of the employee base sits in the 'Average' performance band.

4. HR Action Plan & Talent Retention Strategy

Sales Exit Diagnostics: Conduct targeted exit interviews and review incentive structures in Sales.
Training Optimization: Re-align training curricula to elevate the 50% average tier into high performers.
Attendance Early-Warning: Monitor attendance dips as a predictive indicator of potential attrition.

FEATURED PROJECT 02 Tableau Analytics

HR Workforce & Performance Dashboard

Analyzed 2,500 employee records to examine headcount distribution, voluntary turnover, attendance patterns, training impact, and salary band equity across departments.

2,500 Employee Records

27.8% Sales Attrition (Highest)

IT Headcount Largest Department

Positive Attendance-Performance Link

                      Critical Finding: Sales turnover is disproportionately high at 27.8%, while attendance showed a strong positive association with high performance ratings.
                    

                      Core Recommendation: Launch deeper qualitative analysis into Sales turnover drivers and strategically recalibrate training investments.
                    

Tableau Calculated Fields Scatter Plots Treemaps Data Analysis

Interactive View

Insurance Claims Power BI Dashboard Screenshot

Power BI Desktop

Project Presentation Deck: Insurance Claims & Risk Analytics

In-Site Deck Viewer

POWER BI CLAIMS DECK

Case Study: Insurance Claims Exposure, Fraud Detection & Settlement Slide 1 / 4

1. Executive Overview & Financial Exposure

Analyzed 2,000 insurance claims representing $65.65M in financial value to evaluate claims processing health, fraud incidence, and settlement speeds.

$65.65MTotal Exposure

2,000Claims Analyzed

139Confirmed Fraud

271Pending Backlog

2. Claim Approval & Backlog Dynamics

Approximately two-thirds of claims are successfully approved, while 271 claims remain pending and 344 require deeper investigation.

Investigation requirement is a risk indicator, distinct from confirmed fraud.
Identified specific branch clusters where claim settlement takes up to 45% longer.

3. Financial Risk & Claim-to-Premium Ratio

Tracked Claim-to-Premium ratios across policy types to pinpoint portfolios experiencing acute underwriting strain.

Higher claim severity policy types necessitate tighter reserve allocations.
Geographic mapping highlighted fraud clustering in high-volume metropolitan branches.

4. Underwriting & Settlement Optimization

Automate Low-Risk Approvals: Fast-track clean claims under $5,000 to slash settlement cycle times.
Targeted Underwriting Review: Adjust premiums on policy types where Claim-to-Premium ratio nears 1.0.
Branch Risk Audits: Institute enhanced verification protocols for high-exposure regional branches.

FEATURED PROJECT 03 Power BI Modeling

Insurance Claims & Risk Analytics Dashboard

Multi-page Power BI dashboard evaluating $65.65M in claim value across 2,000 claims, tracking financial exposure, branch concentration, fraud flags, and settlement latency.

$65.65M Total Claim Value

139 Cases Confirmed Fraud Flags

344 Cases Require Investigation

271 Cases Pending Review

                      Critical Finding: 139 confirmed fraud claims and 344 cases requiring investigation account for significant financial exposure across select branches.
                    

                      Core Recommendation: Monitor branch-level Claim-to-Premium ratios closely and implement automated straight-through processing for low-risk claims.
                    

Power BI Data Modeling DAX Geographic Maps Risk Analysis

Interactive View

COMPLETE PORTFOLIO

All Analytics Projects

A full spectrum of 7 data analytics and financial modeling projects across Power BI, Tableau, Excel, and statistical modeling.

Excel Featured

Banking Customer Satisfaction Dashboard

Analyzed 1,200 complaints to identify resolution gaps, complaint categories, CSAT ratings, and fraud bottleneck resolution times.

1,200 Complaints · 783 Resolved (65.3%)

Excel Pivot Tables Pivot Charts

Tableau Featured

HR Workforce & Performance Dashboard

Analyzed 2,500 employee records to assess headcount composition, department attrition, attendance patterns, and salary distributions.

2,500 Records · 27.8% Sales Attrition

Tableau Calculated Fields Scatter Plot

Power BI Featured

Insurance Claims & Risk Analytics

Evaluated 2,000 claims worth $65.65M, tracking financial exposure, branch geographic concentration, fraud incidence, and settlement speeds.

$65.65M Value · 139 Confirmed Fraud

Power BI DAX Data Modeling

Power BI Analytics

Northwind Sales & Customer Analytics

Engineered an interactive Power BI dashboard using the Northwind dataset to analyze customer lifetime value, order fulfillment, product margins, and sales velocity.

Star Schema · Advanced DAX Measures

Power BI DAX Data Modeling

Tableau BI Dashboard

Retail Business Intelligence Dashboard

Interactive Tableau dashboard analyzing omnichannel retail sales, profit margins, customer segmentation, discount sensitivity, and regional product demand.

Regional Margin Analysis · Cohort Filters

Tableau Calculated Fields LOD

Excel Reporting

Interactive Sales Performance Dashboard

Dynamic sales tracking dashboard utilizing Pivot Tables, Pivot Charts, XLOOKUP, INDEX-MATCH, and custom slicers for real-time executive KPI reporting.

Automated Reporting · Dynamic Slicers

Excel Pivot Charts Formulas

MBA Thesis Financial Modeling

Working Capital Analysis in Food Industry

In-depth financial and profitability analysis across 20 listed food companies using liquidity ratio analysis, cash conversion cycle modeling, and regression in E-Views.

20 Listed Companies · Ratio & Trend Modeling

Excel E-Views Ratio Analysis

INTERACTIVE DASHBOARD HUB

Explore the Live Dashboards

Directly interact with responsive dashboard containers designed for executive analysis and operational monitoring.

TOTAL COMPLAINTS 1,200 +5.2% vs Prev Year

RESOLVED 783 65.3% Resolution Rate

PENDING / IN-PROGRESS 417 34.7% Pending Queue

AVG CUSTOMER RATING 3.22 / 5 ★★★☆☆ (1,200 ratings)

Resolution Status Proportion Donut: Composition

1,200 Complaints

Resolved: 783 (65%)

In-Progress: 417 (35%)

Complaint Type Breakdown Bar: Category Comparison

Fraud Investigation

245 (Highest)

Billing & Charges

188

Card Issues

163

Loan Inquiries

122

Online Banking

95

Monthly Complaint Volume Trend Line: Trend Over Time

JanMarMayJulSepNovDec

Avg Resolution Time (Days) Bar: Duration Comparison

Fraud Investigation

14.2 Days (Slowest)

Loan Disputes

8.5 Days

Billing Errors

5.8 Days

Online Banking

3.1 Days (Fastest)

TOTAL HEADCOUNT 2,500 Across 6 Departments

SALES ATTRITION RATE 27.8% Highest Org-wide Turnover

AVG PERFORMANCE 3.8 / 5 Balanced Normal Distribution

SALARY BANDS 4 Tiers Equitable Distribution

Department Attrition Rate (%) Bar: Compare Attrition

Sales

27.8%

Marketing

18.5%

Engineering

15.2%

Operations

12.1%

IT & Support

7.6% (Lowest)

Attendance % vs Performance Score Scatter: Association Analysis

60% Attendance75%90%100% Attendance

TOTAL CLAIMS VALUE $65.65M 2,000 Policies Evaluated

CONFIRMED FRAUD 139 Claims $4.1M Direct Exposure

PENDING CLAIMS 271 Claims Under Risk Assessment

AVG SETTLEMENT TIME 29 Days Target: < 25 Days

Claim Status Distribution Donut: Status Ratio

2,000 Claims

Approved: 1,010 (50.5%)

Open: 650 (32.5%)

Pending: 271 (13.5%)

Fraud Flag: 69 (3.5%)

Claim-to-Premium Ratio by Region Bar: Risk Concentration

North Region

84% (High Pressure)

South Region

71%

East Region

63%

West Region

57%

Central Region

30% (Healthy)

CAREER BACKGROUND

Professional Experience & Education

A proven track record of operational governance in multinational banking coupled with strong academic and certification credentials.

Work Experience

Customer Service Expert

Australian New Zealand Bank (ANZ)

04/2019 – 08/2025 · 6+ Yrs

Bangalore, India

Delivered business-critical operations, application support, and incident governance across banking platforms while maintaining stringent SLA compliance and reporting standards.

Application & SLA Incident Management: Serviced, maintained, and supported core banking applications, ensuring SLA-driven issue resolution and incident lifecycle tracking.
Access Administration & Governance: Managed user access requests, permission provisioning, modifications, deletions, and account validation following strict compliance workflows.
Parameter & System Maintenance: Executed approved interest rate and parameter updates, performed system maintenance, and provided key inputs for BRDs and SOP documentation.
Operational Intelligence Reporting: Compiled daily reports tracking cases received, resolved, and pending backlogs, collaborating with internal operations teams to streamline throughput.

Download Full ANZ Experience & CV

Education & Certifications

Master of Business Administration (MBA)

Ramaiah University of Applied Sciences

2016 – 2018

Specialization: Financial Management

Focused on corporate finance, financial modeling, ratio analysis, and quantitative decision methods.

Bachelor of Commerce (B.Com)

San College of Arts and Science

2013 – 2016

Specialization: Computer Applications

Studied business accounting, database concepts, programming basics, and business management.

Professional Certifications

Advanced Training in AI-Driven Data Analytics

Skill Mount (KHDA Certified) · 05/2026 – Present

Data Analytics Certification

Cokonet Academy · 11/2025 – 04/2026

Complete Business Analytics Certification Program

CoachX · 2024 – 2025

ANALYTICAL APPROACH & RATIONALE

Frequently Asked Questions

Insights into my analytical philosophy, chart selection logic, and business problem-solving methodology.

How does your 6+ years banking background make you a better data analyst?

Having worked directly on banking applications, SLA tracking, compliance, and user workflows at ANZ, I don't treat data as abstract numbers. I understand the operational friction behind delays, the compliance requirements governing financial data, and how business decisions impact actual stakeholders. This allows me to build dashboards focused on answering business questions rather than simply generating colorful charts.

What is your chart selection framework ("Why this chart?")

I choose chart types strictly based on the cognitive purpose of the business metric:

Donut / Pie: Reserved for proportion and composition of a whole (e.g. Resolved vs In-Progress status).
Bar / Column: Category comparisons and ranking (e.g. complaint volumes or department attrition).
Line Chart: Time-series trends and seasonal patterns across months.
Scatter Plot: Evaluating relationships and associations between two numerical variables (e.g. Attendance vs Performance).
Geographic Map: Identifying geographic exposure and regional fraud clustering.
KPI Cards: High-priority headline metrics for rapid executive consumption.

What is your end-to-end data analytics workflow?

Every project follows a structured 5-step lifecycle: (1) Problem Framing: Clarifying the key business questions and KPIs; (2) Data Extraction & Cleaning: Handling missing values, standardizing formats, and data modeling in SQL/Pandas/Power Query; (3) Exploratory Analysis: Identifying correlations, anomalies, and distributions; (4) Visual Storytelling: Designing intuitive, uncluttered dashboards with dynamic filters; and (5) Strategic Recommendations: Translating insights into pragmatic next steps for decision-makers.

Are you available for full-time or contract Data Analyst roles?

Yes, I am actively seeking full-time Data Analyst and Business Intelligence opportunities where I can leverage my banking domain background, Excel/Power BI/Tableau dashboarding capabilities, and SQL/Python analytical skills to solve challenging business problems. I am based in Bangalore, India and open to on-site, hybrid, or remote opportunities.

GET IN TOUCH

Let's Talk About Data

Interested in collaborating, discussing an opportunity, or reviewing full dashboard walkthroughs? Reach out below!

Contact Information

Feel free to connect via email, phone, or LinkedIn. I typically respond within 24 hours.

Email Address sukanyasuresh26@yahoo.in

Phone / WhatsApp +91 9544661377

LinkedIn Profile linkedin.com/in/sukanniasuresh

Location Bangalore, Karnataka, India

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Hi! I'm Sukannia Suresh, turning Data into Decisions.

From Banking Operations to Data Analytics

Bridging Real-World Business with Data

Core Analytical Stack

Tools & Technologies I Work With

BI & Data Visualization

SQL & Data Querying

Python & Scripting

Data Analytics & Modeling

Business Domain & Operations

Collaboration & Strategy

High-Impact Analytics Projects

1. Executive Summary & Problem Statement

2. Complaint Type & Resolution Analysis

3. Customer Satisfaction Diagnostics

4. Strategic Recommendations & Action Plan

Banking Customer Satisfaction Dashboard

1. Executive Summary & Workforce Scope

2. Department Attrition Disparities

3. Attendance & Training vs Performance

4. HR Action Plan & Talent Retention Strategy

HR Workforce & Performance Dashboard

1. Executive Overview & Financial Exposure

2. Claim Approval & Backlog Dynamics

3. Financial Risk & Claim-to-Premium Ratio

4. Underwriting & Settlement Optimization

Insurance Claims & Risk Analytics Dashboard

All Analytics Projects

Banking Customer Satisfaction Dashboard

HR Workforce & Performance Dashboard

Insurance Claims & Risk Analytics

Northwind Sales & Customer Analytics

Retail Business Intelligence Dashboard

Interactive Sales Performance Dashboard

Working Capital Analysis in Food Industry

Explore the Live Dashboards

Professional Experience & Education

Work Experience

Customer Service Expert

Education & Certifications

Master of Business Administration (MBA)

Bachelor of Commerce (B.Com)

Professional Certifications

Frequently Asked Questions

Your Data, My Expertise.Let's Create Exceptional Value.

Let's Talk About Data

Contact Information

Send a Direct Message

Hi! I'm Sukannia Suresh,
turning Data into Decisions.

Your Data, My Expertise.
Let's Create Exceptional Value.