Beyond Resume

"BI is About Insights, Not Charts" - Ankita Das on What Really Matters in Data VisualizationMost people focus on making dashboards look good. Ankita Das focuses on making them meaningful.In this clip from Beyond Resume, Ankita explains why the real foundation of Business Intelligence isn't chart aesthetics—it's the backend data modeling that makes insights possible.

"Mistakes Boost My Confidence" - How Ankita Das Transformed Her Relationship with Failure

Ankita Das, Business Intelligence Expert, used to be afraid of challenges and mistakes. Today, she embraces them as her primary learning tool.

In this clip from Beyond Resume, Ankita shares the mindset shift that changed her career trajectory.

🎯 WHAT ANKITA SHARES:

- Why she was initially afraid to face challenges and make mistakes

- The realization that all real learning comes from resolving mistakes

- How mistakes build confidence and lead to taking ownership

- The shift from fear-based thinking to curiosity-based problem-solving

💡 KEY QUOTE:

"Whenever I learn something new, it comes from mistakes—and resolving those mistakes boosts my confidence. That confidence led me to explore more, take ownership of my work, and now I approach every problem with a mindset of curiosity instead of fear."

🎙️ FULL EPISODE: [Link to full episode]

📌 ABOUT ANKITA DAS:

Ankita is a Business Intelligence Expert specializing in Power BI and Tableau, helping organizations transform data into actionable insights.

📌 ABOUT BEYOND RESUME:

Where careers and analytics come alive. Host Kausik Kumar explores the intersection of innovation and human experience with leaders and rising talents in analytics and AI.

🔔 SUBSCRIBE for more insights from analytics and AI professionals.

#GrowthMindset #BusinessIntelligence #CareerGrowth #Mistakes #Learning #BeyondResume #DataScience

FROM ECONOMICS TO BI EXPERT: Ankita Das on Overcoming Barriers & Building Strong FoundationsAnkita Das didn't start with a coding background. She came from a Bengali medium education and felt nervous speaking English. She was preparing for government jobs that didn't align with her interests.But she made a choice: Follow her passion for data, numbers, and creating real-world impact.In this Beyond Resume conversation, Ankita shares her journey from Economics graduate to Business Intelligence expert—and the lessons she learned along the way.🎯 WHAT WE DISCUSS:→ The moment Ankita realized government jobs weren't her path (00:00)→ How she discovered analytics and data science in 2020 (03:15)→ Overcoming language barriers and lack of coding knowledge (08:30)→ The power of consistency and compounding in skill development (12:45)→ Why data modeling is more important than dashboard aesthetics (18:20)→ Walking away from MNC offers that didn't match her interests (24:10)→ The real purpose of BI: Insights, not just charts (28:45)→ How remote work shaped her collaboration approach (32:00)💡 KEY TAKEAWAYS:- "Most people think BI is about making charts. It's not. It's about revealing insights that drive decisions."- "Whenever I learn something new, it comes from mistakes—and resolving those mistakes boosts my confidence."- "Doing things where your interests don't match is scarier than anything."- "A good dashboard always starts with a good backend."🎙️ ABOUT BEYOND RESUME:Beyond Resume explores the intersection of innovation and human experience in analytics and AI. Host Kausik Kumar sits down with leaders, rising talents, and change-makers to uncover the stories behind the resumes.📌 CONNECT WITH ANKITA DAS:LinkedIn: https://www.linkedin.com/in/ankita-das-7339aa123/📌 CONNECT WITH KAUSIK KUMAR:LinkedIn: https://www.linkedin.com/in/kausik-kumar-a2b5774/🔔 SUBSCRIBE for more conversations with analytics and AI leaders shaping the future of data.#BusinessIntelligence #DataVisualization #PowerBI #Tableau #CareerGrowth #Analytics #DataScience #BeyondResume #DataModeling #BIExpert

"At a time when we're hearing lots of negativity, reading Factfulness and being reminded to think rationally and look at the facts was like a breath of fresh air."

Lindsay Pellow on the book that challenged her biases - even after 25 years in data science.

Factfulness by Hans Rosling starts with a quiz about global trends. Lindsay got a low score. Most people do.

The data shows:

- Lower percentage living in poverty now vs. 30-40 years ago

- Higher percentage of girls completing school

- Deaths from natural disasters less than half what they were 100 years ago

The gap between what we believe and what the data shows is massive.

Lindsay's insight: Even data professionals have biases that blind them to facts. "You learn about your own biases first, and I got a pretty low score."

The reminder: Return to what we're supposed to be good at - looking at actual data, not our feelings about data.

In a world of overwhelming negativity, Factfulness is evidence-based hope. Not wishful thinking. Measurable progress.

The world has problems. But we're solving them faster than we think.

From Beyond Resume with Kausik Kumar.

"A few years ago data was finally front and centre. Now developers are the group everyone wants. But we need both, working together, to develop better products."

Lindsay Pellow on why data vs. tech competition misses the point.

The problem she saw: Tech team building a platform that could count "how many customers did thing X" but not identify WHICH customers. Result? Can't understand how high-value customers use the product. Flying blind on whether tech drives value.

The solution she implemented: Data team working alongside tech team from day one. Data professionals involved in choosing solutions, measuring impact, planning future value. Both teams learning from each other.

Result: Smoother implementation. Better product.

Lindsay's witnessed 25 years of evolution: from physical catalogues and call centres to the UK's biggest online retailer. Customer experience is now driven by technology - but only businesses using data to inform and understand that technology are truly succeeding.

The trend: First data science was hot. Now developers are. The mistake: thinking it's either/or. The reality: we need both.

From Beyond Resume with Kausik Kumar.

"I only knew operational research from a test they gave me. But that test captured my interest - using maths to solve real problems."

Lindsay Pellow on how a borrowed typewriter, her mum's timing, and a single test launched a 25-year data science career.

She wanted to be a doctor. Didn't get the grades. Twice. Studied maths instead. Had no idea what to do after university.

Then her mum, who worked in a call centre, spotted a job ad on the notice board - for an "operational research analyst." The closing date? That Friday. Lindsay asked if she could deliver her application over the weekend. They said yes.

She typed a CV on a borrowed electronic typewriter (no computer at home), posted it through the door on Sunday. The format actually made it stand out.

She still didn't know what operational research was. But they gave her a test: use data to solve fraud detection. The test captured her interest - the idea of using maths to solve real business problems.

When asked in the interview "what does operational research mean to you," she could answer - because of that test.

She got the job. The rest is history. 25 years later, she's one of the most loved leaders in data science.

The lesson: The best careers often begin accidentally. Not with perfect plans, but with curiosity meeting opportunity.

From Beyond Resume with Kausik Kumar.

"Put simply, be the leader you want to have."

Lindsay Pellow on what makes someone a loved leader in data science - not just respected, but genuinely loved.

Lindsay and I worked together at HSBC over a decade ago. She was one of the most loved leaders I've encountered. This conversation explores why, through 25 years of lessons in human-centered data science leadership.

KEY TOPICS:

- The accidental start: How a borrowed typewriter and her mum's timing launched a 25-year career

- The Co-op lesson: Getting humbled when she focused on outcomes instead of understanding people's workload and priorities

- Enabling teams: Why telling people what to do is boring and how to embrace their ideas instead

- Adapting leadership style: Different 1-2-1 formats for different personalities

- Data + Tech partnerships: Why both need to work together, not compete

- Beyond revenue: Using data to measure social impact at a photography gallery

- Building relationships: The most important skill in data science

MEMORABLE MOMENTS:

→ "Several times my team members were saying 'but who's going to do the analysis?' and I was saying 'I can still code, you know!'"

→ "1-2-1s belong to the individual, not the manager"

→ "Anyone who is contributing is welcome - I don't believe in hierarchy"

→ "When team members technically surpass you and take over stakeholder relationships, that's a win-win"

→ "Be the gatekeeper when needed - your team needs to know you have their back"

Lindsay's leadership philosophy isn't about grand vision speeches. It's about small, consistent choices: adapting to personalities, clearing obstacles, enabling growth, being transparent about strategy, and understanding that everyone works differently.

Her career spans retail, financial services, affiliate marketing, and now the not-for-profit sector serving on a photography gallery board. She's seen data science evolve from mainframe printouts to real-time AI. But what hasn't changed: the importance of putting people first.

If you're leading a team, building one, or wondering what human-centered leadership actually looks like in data science - this episode is for you.

From Beyond Resume with Kausik Kumar - where careers and analytics come alive.

Full episode available on all platforms.

Sanmita Sengupta shares one of the most vulnerable moments of her career: blabbering incoherently in a high-stakes regulatory meeting with significant RWA release on the line.

A simple technical question. No preparation. An incoherent answer. Coming out of the meeting "red-faced" with her manager's "choice words" ringing in her ears.

But here's what matters: what she did next. Acknowledged the mistake openly. Started remediation within the hour. Prepared a one-slide comparison. Sent it over quickly. Model approved in two weeks.

Three lessons: Meticulous preparation matters. Accountability is everything. Regulators are willing to collaborate if you allow them to.

The way you handle failure matters more than the failure itself.

From Beyond Resume with Kausik Kumar.

Full episode available on all podcast platforms.

Sanmita Sengupta traces the evolution of credit risk frameworks over two decades - showing how each major financial crisis fundamentally reshaped how banks assess risk.

From Basel II's risk-based approach to the 2008 Global Financial Crisis that exposed backward-looking model failures, to IFRS 9's forward-looking expected credit loss framework, to Basel 3.1's push for consistency - every framework was written in the aftermath of disaster.

Key insight: Credit risk professionals need to stay informed about regulatory thought process and emerging risks. The next evolution (climate risk, AI-ML transparency) is already here.

Are we getting ahead of the next crisis, or waiting for it to write the next framework?

From Beyond Resume with Kausik Kumar.

Full episode available on all podcast platforms.

Sanmita Sengupta explains the fundamental challenge facing credit risk modeling today: incorporating climate risk when banks don't collect the data they need.

A 30-year mortgage needs to consider if the property will go underwater in 20 years - but banks don't have flood risk data, sea level projections, or physical climate scores. Regulators are demanding transparency before the infrastructure exists.

The solution? Partner with universities and climate research organizations for physical risk scores that can integrate into traditional credit models.

Climate risk integration isn't optional anymore - it's reshaping how credit risk works.

From Beyond Resume with Kausik Kumar.

Full episode available on all podcast platforms.