Mentorship Matters: Upskilling, Innovation and Career Tips from an Analytics Lead

My Data Guest — An Interview with Riddhima from Saarthee

Rosaria Silipo
Low Code for Data Science
8 min readJan 12, 2024


Co-interviewer: Alex Quintana

My Data Guest — An Interview with Riddhima from Saarthee

It was my pleasure to interview Riddhima as part of the My Data Guest interview series. In our conversation with her, we delved into the significance of mentors in the realm of data science. Riddhima shared profound insights from her journey with KNIME both as a student and as a trainer, and provided her perspective as a talented professional on the future landscape of data science.

Riddhima is currently the Analytics Lead at Saarthee (Philadelphia, US). She has been working as a consultant at Saarthee for the whole Analytics Value Chain –Data Engineering, Analysis, Strategy and Consulting along with Data Science– for more than 8 years.

Rosaria: As an Analytics Lead leading a group of data analysts, what exactly does your group do?

Riddhima: At Saarthee, we provide data-driven solutions across all aspects of the analytics value chain. We’ve built a suite of dashboards, undertaken data engineering projects, and engaged in data modeling. We can say we have covered everything in the realm of data science. I’m proud of my team –a group of strong data analysts, data scientists, and data engineers.

Rosaria: That’s impressive! Is Saarthee solely a data analytics company, or is there more to its business?

Riddhima: Saarthee is a data analytics and management consulting company. It was founded by Mrinal Prasad and Shikha Miglani, both with over 20–25 years of experience in data analytics and other various industries. The name “Saarthee” comes from a Sanskrit word meaning mentor, guide and trusted companion. This philosophy is embedded in our organization, with each team and project led by a senior principal serving as a mentor and guide both for the team and the stakeholders.

Rosaria: How did you come across KNIME? What convinced you to use it for data analytics and consulting?

Riddhima: My mentor Mrinal, who is also a co-founder at Saarthee, introduced me to KNIME –the no-code/low-code platform where you can drag and drop nodes to create an entire workflow. The agility and versatility it offered made me realize it would make my life easier. After creating my first workflow, there was no looking back for me.

Rosaria: You mentioned that KNIME made your life easier. How did that play out?

Riddhima: KNIME made my work faster due to its agility and ease of use. It enhanced accuracy through robust data quality checks, allowing us to identify and rectify issues promptly, something crucial in our stream of work. Because of how nodes are designed, and the ability to look at the output on each step, I can quickly identify where the problem lies, without having to go through many lines of code.

Rosaria: One question new users are always interested in is how long does it take to move from a beginner to a proficient level. What was your experience?

Riddhima: Considering my background in computer science, I probably have learned KNIME faster. However, I have worked with people without prior coding experience and it typically takes them around 4 to 6 weeks to reach a proficient level. In the first two weeks, they can already create basic workflows. I’d like to add that there are always new nodes and new features coming out, so the learning process never stops.

Rosaria: Since you mention new nodes coming out, what is your favorite feature of the new KNIME 5.2 release?

Riddhima: Certainly, the integration with AI, specifically the K-AI assistant chatbot. That feature caught my interest after a demo at the KNIME DataHop in New York, so I’m looking forward to incorporating it into my workflows.

Rosaria: How many people did you train with KNIME?

Riddhima: We set up a Learning Management System and everyone who joins Saarthee has to go through it, so I would say overall we trained around 60 new users.

Rosaria: That’s a very good sample, so you definitely talk from experience when you say it takes around two to four weeks to become proficient in KNIME. Speaking of the upskilling initiative, can you provide more details about Saarthee’s Learning Management System and how it contributes to ongoing education?

Riddhima: Our Learning Management System at Saarthee offers a range of modular courses designed with real-life use cases encountered in our day-to-day operations. We cover subjects such as data engineering, modeling, SQL, and other various tools. LMS is the brainchild of our CEO and Co-founder Shikha Miglani, her idea was to create a robust learning platform with modular courses proficient enough to train individuals across all aspects of the Analytics Value chain

We actively encourage our team members to explore and engage in continuous learning, providing them with access to the latest courses and tools to stay current in the rapidly evolving field. We drew inspiration from the KNIME courses and we integrated them into our knowledge base, enhancing the learning experience for our team members. Through the incorporation of quizzes and self-assessment features, our LMS not only facilitates skill development but also contributes significantly to the upskilling process.

Rosaria: As someone who has organized upskilling courses, what advice would you give to a KNIME beginner?

Riddhima: Start with the self-paced courses KNIME offers for beginners. They are extremely helpful to get a basic understanding of the platform and to grasp fundamental data science concepts. Another piece of advice would be talking to people that already adopted KNIME and see what they were able to implement with it. Having to deal with some real life scenarios definitely will kickstart your learning journey.

Alexandra: Let’s now briefly shift to the business talk. Why did you decide to formally partner with KNIME?

Riddhima: I have a very short answer: KNIME does it all. KNIME supports all stages of the data life cycle. If we need to do some modeling, to perform some data engineering or to even pull out a custom report, KNIME performs all of these tasks, and it does so with accuracy. In addition to that, we introduced KNIME to some of our stakeholders, our clients, and they also provided us with very positive feedback about the ease of use of the platform. The future development will keep bringing together our capabilities so, in other words, sky’s the limit.

Alexandra: What sets KNIME apart from other tools?

Riddhima: I believe that the culture you developed at KNIME really is a game changer. When I was at the DataHop, I got to meet a very energetic and cutting-edge team. There is always a proactive response from your side. It is a very good platform for working with our clients and for our own upskilling.

Alexandra: As you look ahead, how do you anticipate your partnership with KNIME evolving, and do you foresee any trends that will drive this partnership forward in the broader data science world?

Riddhima: As I mentioned earlier, we have already introduced KNIME to our stakeholders and that will happen more in the future. We provide the business solutions, and KNIME provides the platform to do so. It’s a perfect match!

Furthermore, at Saarthee we have built some components already and we would like to invest more on that aspect. Perhaps one day we will even develop our own KNIME extension.

Rosaria: What are three three features of KNIME or three nodes of KNIME that you couldn’t do without?

Riddhima: I have many candidates but my top three features are:

  • Flow variables. They enable us to control the flow of the workflow by preventing us from manually changing settings within the nodes when a new execution with different settings is required.
  • Visualizing the output of every node. That really helps with debugging and ensuring data quality.
  • Extensibility. You can easily embed other programming languages like Python or R. Also, you can integrate APIs seamlessly.

Rosaria: I believe flow variables mark the difference between beginners and advanced users.

Despite our best efforts, it’s not common to have women on this podcast. This could be due to the fact that while there are women in data science, they may not be as visible, or it could be that there are not enough women overall in this field. How has your experience been as a woman in the field of data science? Have you faced any hostile working environments?

Riddhima: Working environments may be hostile sometimes but I’m here talking to two strong female colleagues, like yourself and Alex, and I’ve also come across many talented women in the data science world, in our team at Saarthee and in the KNIME team.

At Saarthee gender diversity is a core value. It is not just reflected in our founding team but also in the diversity of our consulting team having more than 50% of women in client facing roles. Our Founder and CEO Shikha Miglani is a passionate believer in gender equality. She is a big supporter and a great mentor to all of us here at Saarthee. I have been fortunate to have started my career in an organization where this principle was organically sewn into the fabric of the organization from the start

Rosaria: Thank you for sharing that. Let’s talk about mistakes and successes. What’s your most memorable mistake from which you’ve learned a valuable lesson?

Riddhima: One significant lesson was during a project where we partnered with another team that was trying to build a data propensity model. In machine learning you always have to keep in mind that you cannot build a good model if you don’t have a clear idea of the population, the dependent and the independent variable. The model seemed to perform very well at first but we later discovered they had used the wrong starting population, resulting in a completely skewed analysis. The lesson I got from this experience is that, regardless of how sophisticated a machine algorithm might be, the starting point is always having the right population, the right dependent variable, and the right independent variable.

Rosaria: Now, let’s shift to success. What’s the project you’re most proud of?

Riddhima: A project close to my heart is the name and address matching tool we developed. KNIME helped me modularize the project. It addressed challenges in data where there’s no specific join key. It helped us bring together different data sets, identify duplicates, and has become the foundation for many other projects.

Rosaria: As the field of data science evolves, what resources do you use to stay up-to-date on the newest trends?

Riddhima: Every morning when I wake up I read the TLDR newsletter to keep me updated on the data world. I rely on social media like LinkedIn and platforms like KDnuggets. I have to point out that KNIME’s close-knitted community shares solutions daily, making it easier to stay updated.

Rosaria: Have you tried the KNIME AI Extension that connects to the AI engine with nodes?

Riddhima: We have used the OpenAI integration provided by KNIME for parsing information out of emails. Plus, I’m looking forward to trying the AI extension this year to complete my full learning circle with KNIME.

Rosaria: Before we say goodbye, the million-dollar question: where do you see the field of data science evolving in the next five to ten years?

Riddhima: With the data volume growing exponentially, I believe AI will have a role in helping building and interpreting model outcomes, but I believe it’s unlikely that it will replace data practitioners. I see a trend towards more domain centric data science, thanks to an ease in using technology brought by AI. It’s hard to tell exactly what is going to happen in this field, but I believe the impact of AI will be revolutionary.

Rosaria: How can our attendees get in touch with you or learn more about your work?

Riddhima: You can connect with me on LinkedIn, and feel free to explore Saarthee’s company profile. We’re also hosting a Data Connect event in Philadelphia on January 17th, 2024 where you can meet our team and co-founders.

Watch the original interview with Riddhima on YouTube.



Rosaria Silipo
Low Code for Data Science

Rosaria has been mining data since her master degree, through her doctorate and job positions after that . She is now a data scientist and KNIME evangelist.