The Benefits of an All-in-One Data Platform

When setting up their data stack, businesses across industries have an important decision to make: whether to adopt an all-in-one data platform or rely on separate vendors for ELT, data warehousing, and BI/visualizations. Using different vendors can allow a company to select specialized tools, potentially leveraging best-of-breed solutions for each component of the data platform. 

However, an all-in-one data platform offers a more comprehensive solution, simpler setup, faster time from signing to insights, and better control and ownership over business data. In this article, we’ll look at common questions and differences between each option, and the benefits your business could see from an all-in-one data platform. 

But we think it’s important to make an informed decision, so first let’s look at the other option yada yada something to introduce why, in a benefits of all-in-one platform article, we’re starting with a totally different topic

Different steps, different vendors

Some companies either choose to go with separate tools, or simply end up with this model by circumstance. Let’s look at a few reasons and benefits to this approach: 

1. Starting small: Small businesses and startups often have limited funds, employees, and bandwidth, so it’s key for them to focus on the most pressing need. If the top priority is getting data consolidated and stored in a secure hub, then they’d start with a data warehouse vendor with the intent to build out their stack when the business is more robust. This leads to using several vendors down the line. 
2. Customization: Using different vendors can allow you to choose best-of-breed solutions for each part of the data platform, and tailor them specifically to your particular business needs. 
3. Specialized Expertise: Specialized vendors, like Fivetran for ETL/ELT, BigQuery for data warehousing, or Tableau for BI/visualizations, dedicate everything to one specific area of a data platform. These solutions benefit businesses with their expertise and industry knowledge, which can result in more advanced features and specific functionalities.

It’s equally important to note the drawbacks of a “one tool per function” model. The more moving parts, the more can go wrong, and we see this in integration. With additional tools comes a higher chance you’ll run into integration and compatibility roadblocks when adding them to your data stack. Using specialized tools can also come with higher costs, and those add up quickly compared to the single cost of an all in one platform. 

One-and-done data

If your business needs include ease of integration and maintenance, keeping costs down, and expertise and support throughout the data platform, an all-in-one solution might be the answer. 

Let’s explore the benefits of an all-in-one data platform, especially to startups and SMBs:

1. Time and cost efficiency: Using one tool (especially a managed one) for everything saves time and costs associated with vendor evaluation, selection, and ongoing management. Working with a single vendor means fewer contracts, fewer relationships to manage, and often better pricing and discounts. If you want to upgrade or add a feature, the vendor you’re already using is often more likely to offer bundled or existing customer discounts, and the decision and setup take much less time than shopping for a separate tool.
2. Seamless integration: A single tool for your data platform negates the need for complex, time-consuming integrations between multiple vendors, reducing potential compatibility issues and ensuring smooth data flow through ELT and data analysis. The less “red tape” within your platform, the faster you get insights from your data. 
3. Simplified management: An all-in-one platform provides a single, consistent dashboard to manage your data. This simplifies the entire data management process since you don't need to navigate between tools and dashboards provided by separate vendors.
4. Consistency: An all-in-one platform provides consistency in data structures, formats, and definitions across the entire data pipeline. This ensures that the data remains consistent throughout the various stages, reducing the risk of data discrepancies or errors that can arise from integrating multiple vendor solutions.
5. Better performance: A tool that offers each part of the data platform specifically designs those pieces to work optimally together, providing enhanced performance compared to disparate systems. The components within the platform (ingestion engine, data warehouse, and visualizations) are tightly integrated, leading to optimized data processing and storage and positively impacting the system performance.
6. Streamlined support: If you use a single tool, you don’t have to worry about chasing down support for issues in different parts of your platform. The support team are experts in the entire platform, and having a single point of contact simplifies troubleshooting.

The choice between an all-in-one platform or multi-vendor approach ultimately depends on your business and cost requirements, scalability needs, and your desired level of integration and simplicity. If your goal is a streamlined data platform and single source of truth that scales as your business grows, an all-in-one solution may be the way to go. Panoply can take your company from zero to insights without the hassle of complex integrations, multiple vendors, or hidden costs.