The Best Data Aggregation Tools & Software Available in 2023

Learn about and uncover the power of top data aggregation tools. Transform raw data into actionable insights and supercharge your decision-making processes.

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Data aggregation is a process that takes raw data, transforms it, and presents it in a summarized format. This process can involve large volumes of data, which is why many businesses rely on software to do the work.

If you’re shopping for a data aggregation tool, you have plenty of options. They include all-in-one data management platforms as well as simple visualization and reporting tools.

Below we highlight 10 tools you can use to aggregate data (and then some). Ultimately, your choice will depend on your business needs and existing data stack.

1. Alteryx

Alteryx is a data science platform that supports self-service analytics. It features out-of-the-box data connectors to Snowflake, Amazon Redshift, and many more, but you can also develop custom connectors via APIs. 

Important features

  • It supports ETL (extract, transform, load) and ELT (extract, load, transform) processes that help you aggregate data and upload it to a warehouse of your choice.

  • Data analytics features enable you to develop predictive models and support other types of advanced insights, such as spatial analysis.

  • You can convert insights into Tableau data extracts to create visualizations.

Pricing

The Alteryx platform is available in two pricing tiers:

  • Designer Cloud from $4,950

  • Designer Desktop from $5,195

2. Databricks

Databricks is a provider of “data lakehouse architecture,” which is a data lake and data warehouse in one. The company’s founders are also the creators of Apache Spark, the big data processing framework.

Important features

  • The lakehouse includes ETL functions that allow you to ingest and transform data from any source.

  • It integrates with business intelligence tools such as Power BI to enable data visualizations. The warehouse also supports data dashboards and visualizations.

  • Helps data scientists and engineers develop advanced AI capabilities

Pricing

Databricks offers pay-as-you-go pricing based on compute usage. 

3. Domo

Domo is a business intelligence and analytics platform. It allows companies to develop business apps, integrate data, run analytics, and establish data governance.

Important features

  • The drag-and-drop ETL tool makes it easy for anyone to manage data, regardless of SQL skills.

  • You can implement controls to limit the level of access to live visualizations and dashboards.

Pricing

Domo’s pricing depends on factors such as your company size, number of users, etc.

4. Keboola

Keboola is a data platform that allows data stakeholders (analysts, engineers, and analytics engineers) to easily work together on analytics projects. It supports data storage, sharing, science, and transformations.

Important features

  • The platform connects to your data sources in a couple of hours.

  • Keboola provides a Snowflake data warehouse for your ETL pipelines, but it can also connect to the warehouse you’re already using.

  • You can transform the data with SQL or by using a script like Python, Julia, R, or OpenRefine.

Pricing

Keboola offers two pricing tiers:

  • Free, with a maximum of 120 minutes of computational runtime in the first month.

  • Enterprise subscription plan. The price of the enterprise plan isn’t publicly available.

5. Looker Studio

Google’s Looker Studio (previously called Data Studio) is a data visualization tool that allows you to design interactive reports and dashboards from raw data.

Important features

  • Looker Studio connects to 800+ data sources and includes 600+ connectors.

  • Easy-to-use interface allows you to quickly build reports. Or you can use a report template and customize it to your liking.

  • You can control whether users have permission to edit, download, or print the report.

Pricing

Looker Studio is free to use. If you’re an enterprise customer using Google Cloud, you can talk to your account manager to get Looker Studio Pro. The pro version includes additional administrative features and technical support.

6. Matillion

Matillion is a data productivity platform. It allows both coders and business users to quickly build data pipelines.

Important features

  • You can aggregate, cleanse, and perform other types of data transformations without coding.

  • The platform automatically scans transformations for errors.

  • Matillion provides pre-built data connectors, but you can also create your own.

Pricing

Matillion uses consumption-based pricing for three types of users:

  • Basic ($2 per credit)

  • Advanced ($2.5 per credit)

  • Enterprise ($2.7 per credit)

7. Power BI

Power BI is Microsoft’s end-to-end business intelligence and data visualization platform. Using it doesn’t require any coding skills, making it suitable for business users.

Important features

  • You can connect raw data from any source and visualize it from one platform.

  • Using the drag-and-drop feature, anyone can easily build custom reports and glean data insights.

  • With the AI feature, Copilot, users can ask data-related questions or explain what kind of insights they’re looking for, and Copilot will answer with a report.

Pricing

Microsoft Power BI is available in two versions: Pro and Premium.

  • Pro: $10 per user per month

  • Premium: $20 per user per month or $4,995 per capacity per month

8. Qlik

Qlik is a business analytics platform with a suite of products that support data integration and insights.

Important features

  • Data integration allows you to break down data silos and consolidate data from hundreds of sources.

  • The Qlik Sense tool uses AI to help you analyze data, pull insights, and even generate predictive analytics.

  • Interactive dashboards allow you to explore data points in more detail.

Pricing

Qlik pricing is different depending on which product you’re using:

  • Qlik Analytics costs $30 per user per month. Enterprise users can contact sales for a custom quote.

  • Qlik Data Integration is available as an on-premise and cloud solution. Pricing isn’t publicly available. 

9. Zoho Analytics

Zoho Analytics is a business intelligence and analytics platform. Businesses use it to consolidate their data, generate insights, and build reports. 

Important features

  • It connects to over 500 data sources, including cloud and on-premise databases. The Live Connect feature allows you to create real-time reports and visualizations without storing any data on Zoho servers.

  • The AI assistant, Zia, features a “conversation mode,” where you can ask data-related questions, and it will respond with insights.

  • The data preparation module enables easy data cleaning, cataloging, and transformation.

Pricing

There are four subscription plans for Zoho Analytics:

  • Basic ($24 per month)

  • Standard ($48 per month)

  • Premium ($115 per month)

  • Enterprise ($455 per month)

10. Twilio Segment makes data work for you

Twilio Segment is a customer data platform (CDP) that can collect, clean, and consolidate data at scale. With over 450 pre-built connectors, and the ability to build custom integrations, Segment helps teams understand and act on their data in real time – all with a single API. 

Let’s dive more into how Twilio Segment aggregates data into unified user profiles and audiences to help build highly personalized customer experiences. 

Identity Resolution

Manually maintaining an identity graph can quickly become complex. Emails, device IDs, primary keys – there are countless ways to identify your users. But how do you link all these identifiers together to ensure you’re recognizing the actions and attributes of a single person (even before they become known in your database)? 

Twilio Segment uses deterministic identity resolution, meaning we require exact matches to unify events into a single profile. This helps eliminate the margin of error that can occur with probabilistic identity resolution, which resolves identity on what it predicts to be true.

You're also able to customize how you merge profiles and identifiers, along with setting custom external_IDs

 

segment-id-resolution
A look inside Segment’s identity resolution

 

Profile API

With the Segment Profile API, teams can programmatically query an entire user or account object (e.g., traits, events, external_IDs) – and we’ve made sure that these queries are completed in 200 milliseconds or less. And this API has been tested at scale, currently handling millions of requests each day. With the Profile API teams can: 

  • Build custom in-app recommendation based on users’ behavioral history.

  • Qualify leads at a faster rate 

  • Create highly personalized experiences across channels

  • And more!

     

profile-api-segment
A look inside Segment’s Profile API

 

SQL Traits

With SQL Traits, you’re able to import customer traits from your data warehouse to Segment (like Redshift, Snowflake, BigQuery, Postgres, and Azure SQL). One of the ways you can use SQL Traits is to transfer historical customer data from before you started using Segment to plug any data gaps.

 

sql-traits-segment
Using SQL traits to access data inside your database or warehouse

 

Audience creation

How do you pinpoint who’s ready to buy, or who’s a churn risk, based on their behavior? Sorting through millions, or even billions, or user events is not the way to do it – especially if you’re trying to launch a timely campaign. 

We’ve built an intuitive, simple UI, to create audiences. Under the hood, we parse this into an AST which allows users to dynamically update their audiences with complex aggregations.

 

segment-audience-creation

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Frequently asked questions

Data aggregation tools combine and summarize data from different databases. Companies then use the summarized data for analysis and to support decision-making. Considering most companies aggregate large volumes of data, a data aggregation software tool is the most efficient way to run this process.

The main methods of data aggregation are:

  • Time aggregation, which gathers data from one source during a set period of time

  • Spatial aggregation, which pulls data from several sources over a period of time

  • Manual aggregation, which requires you to manually extract data and upload it into a data aggregation platform

  • Automated aggregation, which uses a data aggregation tool to export and analyze the data sets

During ETL, data aggregation is applied during the transformation process. Other types of transformations include data filtering and cleansing.

Most data aggregation tools aren’t standalone products but come included in a data integration or analytics solution.

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