ETL in Business Intelligence

Modern business intelligence teams simply cannot afford delays, especially when those delays are caused by data bottlenecks. As these bottlenecks become increasingly intolerable, businesses are looking for solutions. 

In this guide, we’ll explore how ETL has evolved to not only support, but become integral to, cloud-first BI, why outdated ETL processes introduce friction, and how modern ETL tools, like Matillion, accelerate business intelligence insights through automation, scalability, and self-service.

Key Takeaways: 

• ETL remains critical in business intelligence, but traditional approaches introduce costly delays and inefficiencies.
• Modern BI ETL tools eliminate bottlenecks with automation, scalability, and ELT support for cloud data warehouses.
• Tools like Matillion enable faster, more reliable analytics by empowering business users and reducing reliance on engineering.
• Organizations like Western Union are seeing real-world impact: faster data prep, quicker onboarding, and measurable efficiency gains.

How Modern BI ETL Tools Eliminate Bottlenecks

Modern BI teams require actionable data, and they’re constantly looking for reliable ways to get this data faster. Traditional ETL processes often create significant data bottlenecks, due to their slow and often manual nature, which in turn, delays insights and decision-making.

With modern ETL software, these friction points are eliminated. Instead, they are replaced by automation, scalability and cloud-native features, which allow for the faster integration and transformation of data, enabling access to high-quality, actionable data. 

The Matillion Data Productivity Cloud is designed to solve these exact challenges and ensure data is frictionless. 

Built for cloud data platforms like Snowflake, BigQuery, and Redshift, it automates complex data workflows, helping businesses seamlessly integrate and transform data. By empowering business users with a low-code interface and robust automation, Matillion accelerates time-to-insight, removes IT bottlenecks, and enables more agile, data-driven decision-making.

Modern BI ETL tools remove technical bottlenecks, giving analysts faster access to clean, actionable data, without waiting on overburdened IT teams.

Business intelligence and the actionable insights it delivers, live and die by two things: data quality and timeliness. Poor or malformed data leads to misleading insights, while delays in data delivery can mean missed opportunities.

While analytics often gets the spotlight, it’s the ETL (extract, transform, load) process, and the data team behind it, that lays the foundation for successful BI. When that process is slow or overly manual, bottlenecks form. Insights arrive too late. Decisions stall. Momentum is lost.

In today’s cloud-native world, traditional ETL methods can’t keep up. Enterprises need faster, more flexible ways to integrate, prepare, and deliver data, without overloading engineering teams. 

This is where modern ETL tools, such as Matillion’s Data Productivity Cloud shine.

ETL (Extract, Transform, Load) refers to three essential steps in preparing data for analytics:

• Extract data from multiple sources (databases, SaaS apps, APIs)
• Transform it into a usable format (cleaning, filtering, joining)
• Load it into a target system (typically a cloud data warehouse)

In business intelligence, this process ensures data is accurate, consistent, and analysis-ready; powering dashboards, reports, and machine learning models.

While the definition of ETL hasn’t changed, the execution has. In today’s BI landscape, performance, scalability, and automation are no longer nice-to-haves: they’re essential.

Modern ETL tools in business intelligence enable organizations to streamline this entire process. By automating transformations, scaling to meet enterprise demands, and reducing manual overhead, these tools eliminate the delays that slow down traditional BI workflows.

Solutions like Matillion’s Data Productivity Cloud exemplify this evolution. With built-in support for cloud-native ELT, low-code interfaces, and powerful orchestration capabilities, Matillion empowers both data teams and business users to move faster, all without sacrificing control or governance.

By streamlining the process and reducing reliance on IT teams, ETL tools in business intelligence become one of a business’s most important assets, enabling faster, more confident data-driven decisions.

ETL vs. ELT: Why the Shift Matters

Traditionally, ETL workflows moved data through a rigid pipeline: extract it from source systems, transform it in an external engine or staging environment, then load it into a destination like a data warehouse. This approach worked, but only up to a point. It introduced latency, duplicated processing, and often required significant maintenance.

With the rise of modern cloud data platforms like Snowflake, BigQuery, and Databricks, the game changed. These platforms offer powerful, scalable compute, making it far more efficient to extract and load data first, then transform it directly within the warehouse. This modern approach is known as ELT.

For BI teams, this shift matters because:

• It reduces latency and duplication: No more moving data multiple times or transforming it in slow, external engines
• It leverages scalable cloud compute: Transformations run faster and scale with your data
• It simplifies pipelines and increases visibility: Teams get a clear view of transformations, lineage, and outputs — all in one place

Modern tools like Matillion are built for this ELT-first paradigm. They allow teams to design, orchestrate, and run transformations natively in their cloud warehouse of choice, with low-code interfaces that empower analysts and advanced options for engineers who prefer to code. 

When it comes to ETL vs. ELT, this shift matters because it fundamentally changes how quickly and efficiently business intelligence teams can access, transform, and act on their data.

A business intelligence stack is only as strong as the data that feeds it. This means that the data needs to be clean, reliable and ready for action. This is where ETL comes in.

Here’s what is typically included in a BI stack: 

• Sources: SaaS tools, on-premises systems, databases
• Integration (ETL/ELT): where all the data gets unified and prepared
• Cloud Data Warehouse: your central source of truth, think Snowflake, Databricks, etc
• Business Intelligence Tools: dashboards, analytics, even AI models

Without it, you’re left with disconnected data, delayed insights, and frustrated teams who can’t trust what they’re seeing.

It takes raw, messy data and turns it into something clean, validated, and ready to use, delivering it to the right place in the right format. When this step is clunky or manual, it slows everything down. And that ripple effect hits hard at the analytics layer, where people rely on timely, accurate insights.

Modern BI stacks need ETL that’s fast, automated, and scalable. It’s what keeps data flowing smoothly, which keeps analysts and decision-makers moving without roadblocks.

Traditional ETL and Business Intelligence: The Bottlenecks

The world we operate and live in is undergoing a constant state of change – don’t keep up, and you’re left behind. And this is especially true in the competitive business landscape.

Data demands are growing, and yet, many organizations are still relying on outdated ETL tools, homegrown scripts, or hand coding, which simply cannot keep up. While these may have worked in the past, such legacy systems and approaches can introduce some serious friction within the analytics process. 

These inefficiencies all stack up, quickly reducing the agility of your BI team and making it harder to respond quickly to changing business questions, customer needs, or market conditions.

In today’s fast-paced environment, slow and clunky ETL isn’t just a tech issue. It’s a competitive disadvantage.

Business Risks of Outdated ETL

Every day your BI team is stuck waiting for data is a day your competitors get ahead. 

Poor or outdated ETL processes don’t just slow things down, they introduce real, measurable business risks.

• Missed revenue opportunities: when insights arrive too late to act on them
• Delayed product and marketing decisions: impacting your ability to adapt or launch effectively
• Higher engineering overhead: with teams tied up maintaining brittle, manual pipelines
• Frustrated analysts and stakeholders: who can’t get the answers they need, when they need them

These issues aren’t just one-offs either, they’ll compound over time. Each delay chipping away at the overall ROI of your analytics investment, while simultaneously making it more difficult to stay competitive in fast-paced markets. 

Modern ETL and Agile Business Intelligence: What Good Looks Like

But don’t worry, it’s not all doom and gloom, business risks, or bottlenecks.

The good news is that modern ETL tools are purpose-built to tackle these challenges head-on, mitigating risks and replacing them with tangible benefits.

To meet today’s BI demands, your ETL solution needs to offer more than just the basics. It should actively reduce friction and empower teams with the speed, scalability, and control needed to keep data flowing smoothly across your entire stack.

With the right capabilities in place, ETL becomes a powerful business asset, not a bottleneck. 

Your BI team can move faster, reduce maintenance burdens and deliver trusted, timely insights to the business.

All the features we’ve covered – from cloud-native architecture to automation and self-service – come together in Matillion’s Data Productivity Cloud, making it a true game changer when it comes to business intelligence.

Purpose-built for the modern BI stack, Matillion helps teams:

• Move fast with deep cloud data platform integrations (Snowflake, Databricks, Redshift, BigQuery)
• Empower users with a visual, code-optional interface for building and transforming data pipelines
• Automate and orchestrate complex workflows from source to insight
• Connect to virtually any data source with hundreds of pre-built connectors

By eliminating complexity and repetitive engineering work, Matillion gives BI teams the speed, flexibility, and confidence they need to turn data into business outcomes.

• Explore Matillion’s Data Productivity Cloud
• See how it powers Self-Service BI

ETL and Business Intelligence: Real-World Results

Organizations across industries are leveraging Matillion to modernize and accelerate their BI workflows. With Matillion, enterprises can:​

• Cut data preparation times from days to hours, or even minutes
• Empower business users to build their own reports and dashboards
• Reduce reliance on overburdened data engineering teams
• Increase speed-to-insight, driving faster and more confident decisions

But we don’t expect you to just take our word for it, the proof, as they say, is in the pudding. 

A standout example is Western Union, a global leader in cross-border money movement. With a complex mix of legacy systems and global reporting needs, Western Union turned to Matillion to modernize its data infrastructure. By implementing Matillion with Snowflake, they achieved:​

• A centralized data ecosystem built in under 6 months, consolidating sources from across 200 countries
• A flexible, scalable pipeline architecture that enables faster access to reliable, real-time insights
• Greater team efficiency, with reduced reliance on manual processes and legacy tools

You can read the full case study here: Western Union: Success Story

When evaluating ETL platforms for your BI needs, consider the following checklist:

• Cloud-native and scalable?
• ELT support?
• Self-service UX for non-engineers?
• Rich connector ecosystem?
• Built-in orchestration?
• Observability and governance?​

Matillion checks all these boxes, and more, making it a smart investment for modern BI teams seeking to enhance efficiency and drive better business outcomes.

Try Matillion: ETL Without the Bottlenecks

Modern BI teams need modern data integration, it is as simple as that. 

Matillion gives you the speed, control, and scalability to turn your data into insights. Fast.