Data integration is crucial for any business that wants to make data-driven decisions. To deliver clear, actionable insights that drive business growth, you first need a consolidated, standardized view of your data.
Manual data integration isn’t feasible for many organizations, largely due to the time and complexity of processing large amounts of data from multiple different sources. Integrating data manually also comes with the risk of manual data errors, which can lead to issues with data quality and affect the accuracy of business insights.
Working with an automated data integration platform is often the most effective way for businesses to consolidate their disparate data sources, improve the quality and consistency of data, and ultimately lead to better decision-making.
The topic of data integration is broad and has many important aspects that need to be considered.
However, one of the most important areas of data integration is data mapping.
Explained simply, data mapping is the process of matching the different fields from each of your various data sources, standardizing them, and loading them into a target field in your centralized database.
If you’re looking for solutions that can help automate the data mapping process, it’s uncommon to find standalone ‘data mapping tools.’
Instead, data mapping is usually found as a key feature set within an ETL or data integration platform.
So, in this article, we’re going to look at the data mapping functionality available in some of the market-leading data integration tools.
Data mapping tools compared
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Who is it for? |
Tailored for marketers and those managing marketing data. |
Data teams with SQL knowledge that don’t need extensive support. |
Marketing teams that need a simple way to extract and load data. |
Larger enterprises that need data integration and visualization in one platform. |
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Data connectors |
600+ |
160+ |
100+ |
1000+ |
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Data fetch frequency |
Up to every 15 minutes |
Up to every 5 minutes |
Every 24 hours |
Up to every 15 minutes |
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Data mapping functions |
Match and map, Smart Naming Conventions, Join datasets, Versatile Enrichments |
Flexible transformations for teams familiar with SQL. |
Data blending, custom fields. |
Magic ETL, Join datasets, Support for custom SQL queries. |
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G2 Review |
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Clients |
Vodafone, IKEA, Bosch |
Forever21, Spanx, Carwow |
Dyson, Warner Bros, Accenture |
Dell, ESPN, New York Times. |
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Costs |
From €500/mo |
Start for free, pay for what you use. |
From €69 for 11 data sources |
Undisclosed - speak to sales. |
1. Adverity
Adverity is a leading data integration platform that specializes in helping marketing teams make more informed campaign decisions.
One of Adverity’s stand-out features is the wide number of pre-built data connectors it has available, making it easy to connect to more than 600 different marketing sources.
The platform also offers a wide range of out-of-the-box data transformations and enrichments and offers the option for data teams to code their own, enabling businesses to tailor their data in ways that directly align with their specific needs and objectives.
Adverity also has robust data governance features to help improve the quality and integrity of your data and ensure regulatory compliance.
When it comes to data mapping, the Adverity Data Dictionary provides a transparent and user-friendly way to connect and configure each of your data sources during data mapping, enhancing the clarity of understanding and democratization of data across the business.
The Data Dictionary also allows businesses to create calculated fields from data to help provide consistency in the way performance data is viewed and analyzed.
Advanced functionality such as Match and Map helps you improve the quality of your data through the use of ‘find and replace’ instructions for data values, whereas Smart Naming Conventions can enforce naming conventions automatically based on patterns in your data.
If you’re responsible for managing or analyzing marketing data within your business, Adverity has the feature set and functionality to enable you to get your data exactly how you want it.
2. Fivetran
Fivetran is a well-established data integration platform that is known for its flexibility and versatility for businesses that are well-versed in SQL.
However, the platform has limitations in terms of supported data destinations, only currently supporting 14 platforms natively for the loading of consolidated data.
From a data mapping perspective, Fivetran has recently launched “Quickstart Data Models,” which allows you to connect and transform data from 23 different data sources without the need for complex code.
However, for any data sources outside of the Quickstart list, SQL knowledge is required to effectively transform and integrate your data, which may be a potential barrier for some businesses.
3. Supermetrics
Supermetrics is a solution that’s ideal for companies looking for an uncomplicated ‘no frills’ data mapping tool that efficiently loads their data into specific destinations like Google Sheets or Big Query.
Supermetrics is widely used by marketing teams in smaller businesses, and users are quick to praise its ease of use.
However, compared to some of the other solutions on this list, Supermetrics doesn’t quite compete at the same level in terms of the number of pre-built data connectors available and the number of data destinations supported.
The platform has a reasonable number of standard data transformation and enrichment options for data mapping, and it also has the capability to create custom metrics from pre-existing data.
However, while Supermetrics excels as a beginner-friendly platform for mapping and integrating data from popular marketing sources, its features supporting data quality, security, and data democratization may be a barrier for larger businesses.
4. Domo
Domo is a comprehensive data integration platform that has a vast selection of more than 1000 pre-built data connectors to enable you to connect to all your data sources easily.
The platform also impresses when it comes to data governance, with a range of features designed to enhance data quality and ensure data security.
Domo’s Magic ETL tool makes the data mapping process user-friendly and intuitive, enabling you to connect to your data sources and apply transformation rules with a simple drag-and-drop interface.
For more advanced data mapping needs, Domo has support for custom SQL queries and also has the ability to join different data sets.
In terms of drawbacks, some users report finding the platform's extensive features a bit daunting, and smaller businesses might find Domo's pricing model prohibitive.
What should you look for in a data mapping tool?
Connect to all your important data sources
To be able to map data from each of your different data sources quickly and effectively, you need a simple and reliable way to connect to them.
Each data integration solution has a different number of out-of-the-box data connectors - which, in practical terms, means that you’re able to connect to your data without any delays or need for complex coding.
Each of the solutions we’ve listed in this article will be able to connect out-of-the-box to the most popular sources, such as Google Ads, Meta Ads, LinkedIn, Mailchimp, etc.
But for businesses that are using lesser-known marketing platforms, you’re more likely to find success with a solution that has 600+ data connectors compared to one that has 100.
It’s also important to consider if the data mapping tool you’re considering is able to support custom connectors for more obscure channels that don’t have a pre-built connector, or connect to your local data storage.
Out-of-the-box transformations
A key part of data mapping is transforming your data from the different structures and formats held in your data sources into standardized, consistent formats in your data destination.
Each data integration solution has its own set of out-of-the-box transformations and enrichments that can help you quickly and efficiently standardize data.
It’s important to check the transformation capabilities of any data integration platform before signing up. Key transformations to look out for are language translation, currency conversion, date standardization, and location unification.
The terminology “transformations” and “enrichments” are often used interchangeably within the field of data integration, and different platforms refer to things in slightly different ways. Both terms relate to transforming and adding value to your data during the integration process so your centralized source of data is exactly the way you want it.
Code your own transformations
Occasionally, businesses might want to standardize or enrich data in a specific way to suit unique business needs.
It might not be possible to find a data integration platform that has an out-of-the-box transformation to meet those needs.
So, as part of your evaluation of different data integration platforms, ask if their solution has the flexibility to allow you to create your own custom data transformations and enrichments.
Create calculated metrics
Another thing to consider when you’re evaluating different data mapping tools is whether they have the ability to create calculated metrics for ease of analysis.
To illustrate this, let’s use the example of the performance metrics held by different marketing platforms. Some might use CPA, others might use ROI, and others might use ROAS.
For consistent data analysis, you want to measure the performance of each of your campaigns by CPA. But how does this work if your data sources don’t have a CPA metric available?
This is where calculated metrics come in. Using this example, you could create “CPA” as a calculated metric within your data integration platform, taking the marketing spend of each campaign divided by the number of sales.
Data fetch frequency
To help stay ahead of the curve, marketing teams need to make decisions based on the most recent data, taking action based on what’s happening today rather than what happened last week.
For your business to be able to do this, you need to be able to access the freshest data possible, ideally in near real-time.
Every data integration platform has its own fetch frequency, which relates to how often it extracts data from each of your data sources.
For the majority of businesses, solutions like Adverity, with a data fetch frequency of every 15 minutes, are likely to be more than enough.
Map your data accurately and effortlessly with Adverity
Effective data mapping is the foundation on which successful data integration is built.
An accurate data mapping process is essential for making sure all your disparate data sources are brought together correctly in your single source of truth and have the format and structure that makes sense for your business decision-making.
Manual data mapping is not feasible for most businesses — you really need the right data integration platform with robust data mapping capabilities.
Adverity is a leading data integration platform specifically designed for the needs of marketers and those managing marketing data.
With more than 600+ out-of-the-box data connectors, advanced data transformation capabilities, the ability to code your own custom enrichments, functionality to easily create calculated metrics, and a data fetch frequency of every 15 minutes - it meets the data mapping needs of any marketing team that’s looking to improve data-driven decision making.
Read some of our case studies to learn more, or book a demo to experience Adverity.
