The Future of Data Analytics: AI-Driven and Automated

It’s no secret that data analytics has become the backbone of modern business strategy. Yet, as we generate data at unprecedented rates, many organizations find themselves unable to keep up with the complexity and scale required to turn all this data into actionable insights that can further their business interests. 

At Savant, we believe the solution to this problem — and the future of data analytics — lies in automation, accessibility, and empowering the untapped potential of business analysts. Let me explain why this shift is not just necessary but transformative.

The Time for Change Is Now

We generate staggering amounts of data every single day. In 2023, the world produced 120 zettabytes of data. In 2025, that number is expected to exceed 180 zettabytes. For businesses, this represents both an enormous opportunity and a daunting challenge.

The issue isn’t the data itself; it’s our ability to act on it. In a survey by Drexel University in 2023, 77% of organizations cited data-driven decision making as their top priority for analytics programs — a significant jump from 65% just two years prior. For enterprises with over 5,000 employees, this number climbs even higher, standing at 87%. Despite this prioritization, many businesses struggle to keep pace with their ambitions because of the bottleneck created by traditional data analytics approaches.

Analytics platforms have been built with data engineers in mind. These highly skilled professionals are responsible for building pipelines, integrating data from diverse sources, and preparing it for analysis. While critical to the analytics process, their scarcity — just 2 million globally — has created a choke point in analytics operations. Organizations simply cannot hire enough data engineers to meet their ever-growing analytics needs.

The result? Delays, frustrations, lost revenue, and unrealized potential. Analysts and business leaders, who are closest to the problems that need solving, are often stuck waiting weeks — or perhaps even months — for data to be prepared, analyzed, and delivered. Such inefficiency slows decision making and stifles innovation, putting businesses on the back foot.

The status quo in the analytics space is damaging businesses that rely on it. The industry is direly in need of a solution to this problem — and I believe we have one. 

Analyst Empowerment

The key to overcoming this challenge requires a rethinking of the way we approach analytics. Here’s the good news: while there are only 2 million data engineers, there are over 80 million analysts worldwide. These professionals, embedded across business units, have the domain expertise and curiosity needed to drive impactful insights. What they lack are the tools to access and manipulate data independently. That’s where the next wave of analytics innovation must focus.

If we empower analysts to efficiently handle data operations on their own with intuitive, AI-powered tools, we can decentralize data analytics, remove bottlenecks, and unlock tremendous value. This shift isn’t just a workaround for today’s challenges; it’s a vision for a more efficient, scalable, and inclusive approach to analytics.

The Benefits of Analyst-Driven Analytics

Enabling analysts to do what previously only data engineers could will immediately solve the biggest problem facing the data analytics industry today. But there’s more to it than just that. Such a shift uncovers deeper efficiencies, synergies, and opportunities that would come into play. Empowering analysts to take charge of their own data needs has profound implications:

Faster Insights

When analysts have direct access to the data and tools they need, they can rapidly explore ideas, test hypotheses, and iterate on analyses. This agility translates into faster, more informed decisions.

Streamlined Operations

Eliminating dependency on centralized engineering teams removes a major bottleneck. Analysts working within business teams can respond to needs in real time, enabling greater responsiveness and efficiency.

Better Strategic Alignment

Because analysts are closer to the business, they have a deeper understanding of its goals and challenges. This proximity allows them to create more relevant and actionable insights that are aligned with organizational strategy.

Empowerment and Innovation

With the autonomy to experiment, analysts are more likely to feel a sense of ownership, empowerment, and freedom, helping uncover novel insights and creative solutions that drive innovation across the organization.

Scalability and Specialization 

Decentralizing analytics enables teams across the organization to scale their efforts independently. Analysts can also specialize in tools and techniques tailored to their specific domains, leading to more sophisticated and targeted insights.

Optimized Resource Utilization

Freeing data engineers from routine analytics tasks allows them to focus on building and maintaining robust data infrastructure while analysts take on the heavy lifting of deriving insights. This balance leads to more efficient use of resources and significant cost savings.

A New Era of Data Analytics

At Savant, we’ve made it our mission to enable this transformation to self-service analytics. We’re building tools that democratize data analytics, making it accessible to analysts across the organization without requiring advanced technical skills. With the power of AI and automation, we’re closing the gap between the demand for insights and the capacity to deliver them.

Curious about what such a solution would look like? We cover that and much more in our e-book, ‘The Future of Data Analytics: AI-Driven and Automated’. Download now to read all about it!

The future of analytics is one where every business analyst has the power to turn data into action. Are you ready to embrace it?