In the Spotlight: Abirami Karthikeyan on What Companies Need to Know to Unlock Data Success

With over 14 years of experience in IT, particularly in data warehousing and analytics, Abirami Karthikeyan brought a deep wealth of knowledge to her role of Data and Analytics Manager at BlueCloud.??

In this interview, we chatted with Abirami about her career journey, her impact on BlueCloud’s projects and mission, data foundation struggles companies face, and the BlueCloud’s role in helping companies overcome data hurdles.??

The Move to BlueCloud??

Abirami Karthikeyan's story with BlueCloud kicked off in January 2022. Back then, she already had about 11 years of experience in the IT world, all focused on data warehousing and analytics.??

Before BlueCloud, she’d gained much of her domain knowledge while working for major enterprises like TCS (a prominent multinational IT consulting firm). But no matter how rewarding her experiences were, she felt she needed to look for environments where she could grow continuously.??

"Working on long projects with the same tools, day in and day out, was just too predictable. Since the data landscape was evolving fast, I needed an environment where I could have more control over learning new tools, apply new technologies, and take part in constructing broader data strategies.”?

Meeting with Jim Harper, a director at BlueCloud at the time, marked a turning point.??

“At the time, BlueCloud was growing at lightning speed, and it all just clicked. The company promised exactly what I was searching for: freedom to learn, a chance to work on cutting-edge projects, and the opportunity to shake things up in the tech world.”?

Fast forward almost three years, and Abirami is pretty confident that she had made the right choice.??

“It’s been like a crash course—new tools, new projects, and real, hands-on work that’s way beyond just earning a certificate. Plus, I’ve had the chance to work on crafting data strategies for clients, especially using game-changers like Snowflake. BlueCloud turned out to be the perfect place to push my limits, learn non-stop, and have a real say in shaping how organizations handle their data.”?

What’s the Spark in Data Analytics??

For Abirami Karthikeyan, data analytics wasn’t something she set out to pursue intentionally—it sort of found her.??

“You know, it’s funny—data kind of picked me, not the other way around. Back in 2010, at the start of my career, I had options: I could have taken the path of a Java developer or ventured into the data realm. The data project came my way, and I took it.”?

While many professionals in tech switch tracks over time, Abirami stuck with data analytics. Why? Because it’s a field that’s always moving, always growing. New trends pop up, new tools emerge, and there’s always something to learn.??

But it’s not just the ever-changing nature of data that hooks her. Abirami loves seeing the impact of her work.??

“With data, the results aren’t hidden behind layers of code or buried in complex systems. Whether it’s building ETL pipelines or developing dashboards, I get to see firsthand how these tools help analysts drive business decisions and improvements. And now, with AI and machine learning, we’re not just playing in the sandbox—we’re reshaping the whole playground.”?

For Abirami, data analytics isn’t just a job; it’s a space where she can keep growing, stay challenged, and watch her work make a real difference.??

Navigating the Challenges of Data Integration?

There’s a lot of talk about data integration, and it’s always on the roadmap, but when it comes to execution, that’s where things get tricky.??

Abirami believes that the biggest challenge in achieving successful data integration isn’t just about “getting things done but actually doing them right.”?

The goal is clear: execute well and integrate smoothly. But the success of this varies depending on how well you handle the challenges along the way.?

“There’s no one-size-fits-all solution because there are so many moving parts. The challenges you face can range from technology issues to people problems, or even data-related hurdles, where choosing the right tools and platforms is key. Data itself is often messy or siloed, and there’s always the challenge of making sure that data can flow seamlessly between systems.”?

Abirami adds that sometimes organizations are experiencing a vision problem as well.?

“Everyone’s on the same page about what they want, but the execution falls short.”?

Other times, it's a resource challenge—companies may have the vision but lack the financial muscle to roll out large-scale data processing systems.??

Whether it’s getting the tech right, aligning the team, refining processes, or even securing the budget to bring the vision to life, each challenge has its own impact.?

“Throughout the projects I’ve been involved in, we’ve encountered at least one of these challenges at each turn. But when you navigate through these obstacles the right way, that’s when you hit the golden goal—the smooth integration of data that actually drives value for the business.”?

Facing the Data Foundation Struggle: What Companies Really Need to Know

Technology Limitations

Abirami explains that many organizations are held back by technology limitations.??

“Some companies are still relying on legacy systems or on-premises infrastructure, and the tools they have may not be the most optimal for their current needs. Sometimes they end up overspending on tools they don’t fully use, or they lack the infrastructure to manage growing data effectively.”?

Data Challenges

Another big issue is that data needs to evolve over time.??

As organizations grow, merge, or shift their business models, their data requirements change. What worked a decade ago may no longer meet the demands of the business today.?

“The problem is that many organizations end up applying patches on top of outdated systems, creating a patchwork approach instead of building a strong, scalable foundation from scratch.”?

Cultural Resistance to Change

Abirami explains that employees and teams often become deeply attached to legacy systems, and it can be a challenge to get everyone on board with moving to newer technologies.??

Financial Barriers??

Building a strong data foundation can be expensive, and some companies are working with limited budgets or long-term contracts with legacy systems.??

“This makes it even harder to modernize without a huge upfront investment. That’s where the pay-as-you-go model comes in—it’s been a real game-changer. It gives data leaders a way to modernize without needing to blow the budget on a massive overhaul.”?

Leadership Buy-in??

Abirami points out that it takes strong vision and convincing data leaders to make the switch. The fear of ripping out an existing system can hold companies back, and it takes a compelling use case to drive that change.

“At BlueCloud, we help our clients navigate these challenges. Instead of completely ripping everything out, we help them make the switch gradually, so it’s less disruptive and more sustainable in the long run. It’s all about building a solid foundation that can grow with them, not just patching things up.”?

Transforming Data Foundation with BlueCloud?

People-First Approach?

Abirami says that at the heart of any successful project lies the people behind it.??

“Building strong data solutions isn’t just about implementing the latest technologies or using flashy buzzwords; it’s about assembling a comprehensive, skilled team that can support clients through each step of their data journey and help them “rip the band-aid” effectively.”?

A Holistic View on Data Solutions??

Another core strength of BlueCloud is looking at data solutions holistically.??

“If an organization is implementing machine learning (ML) models, it’s not just about achieving advanced technical capabilities. BlueCloud ensures that these models are sustainable, deliver consistent performance, and integrate seamlessly with high-quality data. Our attention to detail helps clients build robust solutions from the ground up, capable of supporting both present and future needs.”?

ROI as a Key Factor?

Budgets are tight, and organizations need to maximize their spending.??

“That’s where our approach shines—we help organizations optimize their costs and scale services through flexible, pay-as-you-use models that make sense.”?

Flexibility. Efficiency. Affordability??

BlueCloud takes this mindset even further by being adaptable in our services.??

“We don’t just offer solutions; we actively participate and collaborate, ensuring our implementations are efficient not just in technology, but in teamwork. It’s this blend of an optimal tech stack and an optimal team that makes BlueCloud truly stand out in every project. We don’t just deliver data solutions; we partner with clients to implement optimal, customized strategies and build solutions that stand the test of time.”

What Emerging Trends Will Shape the Future of Data Analytics?

Looking ahead, Abirami distinguishes five areas that will shape the future of data analytics: sustainable and ethical AI, strong data governance, AI as a service, and an increase in self-service capabilities driven by generative AI.?

“Sustainable AI is about ensuring that the models we develop have a meaningful lifecycle. Companies need to prioritize building solutions that don’t become obsolete in a matter of months, as that wouldn’t be a good return on investment. This means designing models that are adaptable and can evolve with shifting business needs and data landscapes.”?

Ethical AI is another critical area. We’re seeing even industry leaders face challenges in ensuring that their AI practices are ethical.??

“The concept of ethics in AI is complex and can be subjective. Building ethical AI means creating systems that are transparent, fair, and unbiased, and ensuring they align with societal values and regulations. Organizations will need to invest in robust governance frameworks to guide their AI initiatives.”?

Beyond that, data governance and data security are going to stay front and center. Why? Because they support both sustainable and ethical AI by making sure data is managed in a responsible and secure way.?

Abirami adds that another trend to watch is AI as a Service (AIaaS).??

“AI as a Service (AIaaS) allows companies to access AI capabilities without building everything from the ground up. Think of it as a flexible way for businesses to bring powerful analytics into their operations and deliver AI-driven solutions to their customers without massive overhead.”?

And we can’t forget about self-service analytics and generative AI. As tools like chatbots and generative AI become more advanced, more companies will look to make data analysis available to everyone—not just data scientists.?

Envisioning Future Success??

Abirami’s definition of success goes beyond just climbing the career ladder. For her, it’s about making steady progress within the organization and continuously adding value.?

“My goal is to do something better and more innovative each year. It is critical to continuously learn in a field like data analytics, where change is constant, master new tools and deepen my understanding of the latest technological advancements. For me, professional growth means staying ahead, continually enhancing my skill set, and developing my expertise.”?

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Connect with Abirami Karthikeyan to discuss how we can help you transform raw data into actionable insights. ?

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