Today, most business leaders recognize the power of data. According to Salesforce’s Untapped Data Research report, eight in 10 say data is now critical to decision-making.
But awareness is only half of the battle. When it comes to actually using data, many companies still run into challenges—namely, a lack of time, tools, and talent. In fact, Hubspot’s Multiverse Skills Intelligence Report 2024 reveals that employees waste more than 10% of their working time due to skill shortages in predictive modeling, automation, and data analysis. One-third of respondents admit they lack the ability to generate insights from data, per Salesforce’s survey.
Unfortunately for these business leaders, data challenges aren’t going away anytime soon. Actually, they’re multiplying. Data volumes only continue to grow—and Salesforce’s report confirms that nearly one-third of business leaders are already overwhelmed by it. Others cite poor data quality, siloed systems, and a lack of actionable insights among their biggest hurdles.
So, where are you supposed to go from here?
One way businesses are learning to overcome data analytics challenges is to simply stop trying to solve them—instead, they’re outsourcing data analytics to expert partners via Analytics as a Service.
In this post, we break down what Analytics as a Service is, how it works, and when to know if it’s the right fit for your business.
What is Analytics as a Service (AaaS)?
Analytics as a Service (AaaS) is a managed, cloud-based model where businesses can fully outsource data analytics capabilities, including data strategy, data modeling, report authoring, and more. It’s a flexible, on-demand way for businesses to get real value from their data—without the complexity of doing it in house.
Unlike traditional data analytics solutions, AaaS doesn’t require organizations to spend the time, energy, or resources investing in, hiring, and managing an internal team or data experts—nor do you need to build and maintain complex, on-premise infrastructure.
Instead, AaaS lets you adjust and scale your data analytics capabilities as needed, when needed, so you can generate insights faster, more easily, and at a lower cost
What are the Benefits of Using Analytics as a Service?
AaaS helps business leaders who are drowning in a torrent of data turn that data into valuable insights to make better, faster, more informed decisions that solve real-world problems. Most importantly, AaaS enables organizations to leverage their data without the overhead of managing an in-house data team or on-premises analytics infrastructure.
Here are some of the most impactful benefits of using Analytics as a Service:
1. Avoid Large, Upfront Investments in Infrastructure and Staff
Building an internal data team means hiring data engineers, data analysts, report developers, and other specialized roles. That’s in addition to buying and maintaining expensive software and servers. Altogether, that adds up to a significant upfront cost, as well as ongoing expenses to train, support, manage, and maintain your staff and equipment.
AaaS completely removes this burden by giving organizations access to niche, expert skills and modern data analytics infrastructure without the headache or cost of full-time, in-house resources.
Think building an in-house data team is easy? Discover the many factors to consider when hiring a data architect.
2. Deploy Quickly and Start Seeing Results Faster
Traditional analytics projects can take months to deploy, as organizations must assemble in-house data teams, build infrastructure, and develop custom workflows from scratch. But with AaaS, you can skip the laborious setup and jump to insights much faster.
That’s because AaaS is designed for speed. By outsourcing data analytics to a dedicated team of experts, you can get reports and dashboards up and running in weeks instead of quarters. This means you spend less time fiddling with data pipelines and painstakingly cleaning data—and more time actively using it to solve problems, improve performance, and unlock new opportunities for business growth.
3. Easily Expand Analytics Capabilities as Your Business Grows
To say your business will change over time is stating the obvious. Whether you’re launching a new product, entering new markets, or scaling operations, your organization’s priorities and needs will naturally evolve—and your data solutions need to evolve with you.
Compared to more rigid, in-house data solutions that require heavy rework and lengthy timelines to scale, AaaS is designed for flexibility. Its elastic design enables you to scale up or adjust your analytics capabilities as needed, without having to go through the headache of overhauling internal systems or onboarding new staff.
This is particularly advantageous for small- to mid-sized businesses and start-ups who want to tap into data analytics from the start while leaving enough room to scale quickly when ready.
Why is it extra for small companies to build in-house data teams? Explore the State of a Data Team at Small- and Mid-sized Companies.
4. Stay Focused on Business Outcomes, Not Technical Setups
Data analytics is a tool to support your business—it’s not the heart of your business. Rather than spending time worrying about data pipelines and platform maintenance, your energy is better spent serving customers and driving growth.
With in-house data analytics solutions, unfortunately, business leaders often end up wasting a lot of time babysitting dashboards and troubleshooting broken data connections. But when you outsource your analytics to an AaaS provider, you can have the confidence and peace of mind that a dedicated team of experts is taking care of your infrastructure and reporting environment—so you can stay focused on strategy and performance.
5. Reduce Risk with Proven Processes and Expert Support
Data analytics is undeniably advantageous—but there are risks if not implemented correctly.
For example, most prominently, working with poor-quality data can actually do more harm than good and risk leading to misguided decisions and even financial losses. According to the 2023 Forrester Data Culture and Literacy Survey, more than a quarter of global data and analytics professionals estimate that poor-quality data will cost businesses $5+ million per year. Seven percent say that number is more like $25+ million.
AaaS takes away this risk. Rather than adding data analytics to your already never-ending list of business responsibilities, AaaS takes over data analytics for you—with trusted processes, continuous quality assurance, and expert oversight to ensure data is accurate, secure, and actionable. That means fewer bad surprises, more confidence in your reporting, and high-fidelity data to power decision-making that solves problems and moves your business forward.
How Analytics as a Service Works
While delivery models vary, here’s what you can expect when partnering with an AaaS provider:
1. Data Integration: Bring All Your Data Together
The first step is connecting all your systems, such as CRM, ERP, financial software, HR tools, etc.
AaaS solutions then extract, transform, and load (ETL) all of this diverse data into one centralized model to enable unified reporting. This integration process connects the dots between systems to unify fragmented data sources and ensure your data is organized, accessible, and ready to support meaningful analysis and decision-making across your business.
2. Data Management: Ensure Accuracy and Compliance
Next, data gets cleaned, validated, and structured for analysis. This is a critical step. Without clear governance or proper validation, poor data quality can lead to inaccurate reports, misguided decisions, and even compliance risks.
But unfortunately, many business leaders struggle to ensure data quality, accuracy, and compliance. According to a 2024 trends report from Gartner, 34% of data leaders call out their budget as one obstacle holding them back from improving their analytics. AaaS can remove that barrier, unlocking enterprise-level quality without the often prohibitive costs of managing internal data teams and maintaining on-premise infrastructure.
At this time, your AaaS provider also applies governance and security protocols to protect sensitive information and ensure data privacy and regulatory compliance.
3. Analysis & Modeling: Turn Raw Data into Actionable Insights
This is where your data gets transformed from raw information into insights you can actually use to power strategic decision-making and problem-solving.
Your AaaS provider designs and builds models according to your organization’s specific challenges and priorities, such as tracking operational efficiency or forecasting revenue performance.
These models will be the engine behind your reporting, providing the metrics, logic, and structure to enable teams to spot trends, track performance, anticipate risks, and identify new opportunities for growth.
4. Reporting & Visualization: Share Insights Across Your Organization
Per Salesforce’s Untapped Data Research report, 41% of business leaders say they struggle to use data because it’s too complex or not accessible enough. That’s where well-designed reporting and visualization make the difference.
Once your data is modeled, AaaS providers build visual reports and dashboards that bring those models to life. Whether that’s monitoring performance, tracking KPIs, or managing resource allocations, these visualizations are purpose-built to deliver the right insights to the right people to support faster, smarter decision-making.
Plus, when expertly designed, these visualizations enable teams to do more than passively view data; they also empower you to interact with it, filter it, and drill down at the metric level to identify trends and pinpoint issues for targeted improvements.
Want an example of reports in action? Explore Our Top 8 Dashboards for the Insurance Industry.
5. Ongoing Optimization: Improve and Evolve Over Time
Your business isn’t static—and your analytics shouldn’t be either.
One of the biggest advantages of Analytics as a Service is that it’s not a one-and-done project. Instead, your AaaS provider stays with you throughout the life of your analytics solution to continuously monitor, adjust, and evolve your reporting environment as needed to reflect changing business needs, shifting priorities, and new data sources.
Considering Hubspot’s Multiverse Skills Intelligence Report 2024 reports that more than half of business professionals struggle to use data analysis for forecasting, ongoing support is more than helpful—it’s essential. With AaaS, you can count on a responsive team that proactively refines your analytics environment and keeps your reporting aligned for long-term clarity, agility, and impact.
Common Use Cases for Analytics as a Service
Every business has decisions to make and problems to solve. And every decision can be made better and every problem solved faster if businesses have the insights they need to take informed, confident action.
That’s why every business can benefit from data analytics—no matter what industry you’re in and no matter what the problem is.
Here’s a look at a few industry-specific ways organizations can use AaaS:
Industry | Example Use Cases |
Banking & Financial Services | ● Risk modeling ● Fraud detection ● Client profitability |
Healthcare | ● Credential compliance ● Staffing analysis ● Patient outcomes |
Retail & eCommerce | ● Inventory forecasting ● Marketing attribution ● Pricing analysis |
Manufacturing & Supply Chain | ● Production efficiency ● Equipment monitoring ● Quality control |
Insurance | ● Claims analysis ● Underwriting performance ● Policy risk segmentation |
Sales & Marketing | ● Funnel visibility ● Campaign performance ● Lead scoring |
Human Resources | ● Workforce planning ● DEI metrics ● Attrition trends |
Want a closer look at data analytics in action? Explore our Data Stories series, where we show how you can solve any problem in any industry when you turn to the data.
Each use case explores a niche business challenge and demonstrates how a data-driven mindset powers better decision-making, smarter problem-solving, and measurable results.
Because no matter the challenge or the industry, the answer is in the data.
When to Consider Analytics as a Service
Pretty much every industry can benefit from data analytics—but not every business has the resources to manage it in-house. That’s why more business leaders are turning to Analytics as a Service for accessible, expert-level data analytics without the burden of building everything internally.
If any of these sound familiar, AaaS might also be the right fit for your business:
- You don’t have (and don’t want to build) an in-house data analytics team.
- Your reports are inconsistent, slow to produce, or not giving you the answers you need.
- You still rely on time-consuming, laborious spreadsheets or other manual processes for reporting and decision-making.
- Your tools and systems are siloed, making it difficult to get a unified view of performance.
- You know you need to make “data-driven decisions,” but you’re not sure how or where to start.
- You spend more time cleaning and organizing data than actually using it to grow your business.
With AaaS, you can bypass these challenges and jump straight to insights for faster, more informed decision-making.
Want a deeper dive on Managed Analytics Services? Read Managed Analytics Services: What They Include, Who They’re For, and Why They Matter.
Why LeapFrogBI’s Managed Analytics Model Outperforms Traditional AaaS
The modern analytics landscape is ripe with platforms, plug-and-play dashboards, and other analytics support. But a lot of these so-called solutions are little more than cookie-cutter reports and one-size-fits-all that have next to no connection with your organization’s real challenges and operational context.
At LeapFrogBI, we believe off-the-shelf reports aren’t enough.
Our Managed Analytics Services give you more than a few basic charts. We provide a complete, at-your-service data team, a proven methodology built for speed and scale, and a collaborative partnership focused on long-term success.
You get enterprise-class data analytics, tailored to your business model, priorities, and evolving needs—without the complexity or cost of doing it all in house.
Dive deeper into what our Managed Analytics Services can do for you.
Here are the quick takeaways:
Team-Based Expertise
Our Managed Analytics Services give you more than just a tool and one or two analysts. Instead, you get access to an entire data analytics department, including seasoned data engineers, analysts, developers, and BI specialists who work together to design, build, and manage a reporting ecosystem that drives real-world results.
From Day 1, our team acts as an extension of your organization—not just another third-party vendor. We collaborate closely with your stakeholders to align on priorities, adjust quickly, and keep your reporting environment focused on delivering actionable insights.
Custom Solutions
We don’t do cookie-cutter reports or rinse-and-repeat dashboards.
Because of our experience delivering custom solutions for organizations in insurance, healthcare, manufacturing, and more, we understand that data analytics solutions need to be tailored to your business’s specific goals. We work with custom KPIs, and workflows to help you answer real-world questions and solve real-world problems.
LeapFrogBI uses a proven methodology that’s faster and lower-risk than traditional approaches to data analytics. This way we can design and build a custom solution that fits your needs, your teams, and your budget—without unnecessary complexity, expenses, or waste.
Why don’t we use cookie-cutter reports? Learn why off-the-shelf dashboards are never enough.
Scalable Partnership
Inevitably, your business will change over time. And so will your data needs and strategic priorities. We build analytics solutions that can change with it.
From Day 1, we design with flexibility in mind. This enables us to adapt quickly, scale efficiently, and evolve with your organization. Maybe you are expanding to new departments, adding new data sources, or adjusting to meet new goals or market demands.
Our mission is to deliver value quickly while laying the foundation for long-term success so your analytics stay relevant and useful no matter how your business grows.
Common FAQs
What types of analytics are offered in Analytics as a Service?
It depends on your industry and your specific business goals. In general, AaaS can support a wide range of use cases—from operational reporting and KPI tracking to forecasting, benchmarking, and strategic analysis.
But if you’re not sure what you need, that works, too. At LeapFrogBI, we work with you to clarify your objectives and create a solution that goes beyond basic tracking to help solve persistent problems and unlock new opportunities to grow.
How long does it take to see results from Analytics as a Service?
Compared to the months (or more) it takes to hire and train an in-house data analytics team and set up internal infrastructure, you can get started with Analytics as a Service in just a few weeks. While specific timelines do vary based on your current data environment and goals, we move fast. In fact, many of our clients see a 10x ROI within just six months.
Is Analytics as a Service secure?
Our team is required to be HIPAA, HITECH, and data security trained. We use the latest security methods and continuously monitor all processes.
Can Analytics as a Service integrate with my existing systems?
Absolutely. The whole idea behind Analytics as a Service is flexibility. We work with you and the tools already anchored in your business—whether that’s your CRM, ERP, finance platform, or other core systems.
When we build your solution, we bring together siloed data sources into one clean, centralized place so you can spend less time chasing data and toggling between systems and more time using it to drive better decisions.
