The 18 best data management tools for your organization

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‘Data’ has become somewhat of a buzzword. Many organizations are aware of its importance in making better business decisions, but aren’t necessarily managing it in the right way.

A good data management strategy should deliver a single source of truth that can be relied upon and accessed by different teams across an organization, regardless of their technical ability. 

And to reach this point, companies need to get the best data management tools in place. In this post, we’ll list out what we believe these are, covering everything from behavioral data tools to warehousing and reverse ETL. While this list is by no means exhaustive, we hope it will provide a solid starting point to build a data-informed culture at your organization. 

Behavioral data management tools

At a general level, behavioral data describes the interaction between your customers and your organisation. This interaction (or ‘event’) can occur on a website, app, or any other interface that can be tracked. A behavioral data platform helps to collect, validate, and model these events so multiple stakeholders can get the maximum value from the data. 

1. Snowplow

Snowplow is a behavioral data platform that allows you incredible control over how you collect and process real-time, rich behavioral data from different sources. This helps eliminate data silos and streamlines data organization so you can focus on what matters.

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Business intelligence data management tools

BI (Business intelligence) tools allow you to make better strategic decisions by turning your key data into actionable business insights.

2. Tableau

Tableau is a leading Business Intelligence (BI) platform that allows you to build shareable dashboards quickly and explore data from almost any system.

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3. Looker

Looker is a BI platform that allows anyone on your team to explore data and build visually-engaging reports.

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4. Power BI

Power BI by Microsoft provides self-serve analytics for everyone from the individual to the enterprise-level team.

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Customer Data Platform

A Customer Data Platform (CDP) structures data across your entire organization, so you can better operationalize crucial processes, most often services and sales. Whereas behavioral data tools are optimized to model broad and real-time information for many business goals, CDPs are often set up to gather data into distinct user groups so you can target marketing efforts.

5. Segment

Segment is a Customer Data Platform that collects data about every customer touchpoint and allows you to create profiles, audiences, and more. These segments can then be deployed across all of your tools so that you have a complete picture of what customers are doing across disparate sources.

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6. mParticle

mParticle is a CDP that allows teams to provide customized experiences for their customers.

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Data warehouse management tools

A data warehouse is a central repository of information where the bulk of your data will be managed. Having all your volumes of data in one place is critical for analytics, reporting, and building tools.

7. Google Bigquery

Google BigQuery is a multi-cloud data warehouse designed for businesses at scale.

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8. Amazon Redshift

One of the most popular cloud data warehouses, Amazon Redshift offers high performance for businesses of any size.

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9. Snowflake

Snowflake is a popular data warehouse that breaks down silos between your data tools with multiple clouds.

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Product analytics data management tools

Product analytics tools allow you to get user and product insights straight from your data warehouse. It’s similar in some ways to business intelligence tools but allows you to have more complex queries on structures purpose-built for product concerns.

10. Indicative

Indicative is a product analytics platform that allows you to view every part of the customer experience, from journey maps to cohorts.

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11. Rakam

Rakam runs product analytics on your data sources that you can model into insights for your platform.

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Data modelling

Data modelling is the process of aggregating event level data into structured, ‘modelled’ data which is simpler to query.

12. dbt

dbt is a tool that allows business analysts to easily transform and model their data using SQL. It tackles a very specific aspect of the data pipeline, so if you’re wondering if dbt’s the right tool for you, the team has a great blog post explaining precisely who they’ve built it for and why.

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13. dataform

Dataform allows teams to build a single source of truth for all of their company’s data. It has recently joined Google Cloud, so it now bolsters an already impressive suite of data tools in the Google ecosystem.

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ETL and ELT

ETL stands for “extract, transform, load”—it’s the process by which you grab data from a source, make the format and models compatible with where it needs to go, and then stream it into the data warehouse destination.

14. Fivetran

Fivetran is a leading ETL tool that helps teams unify their data systems at scale. With Fivetran, you can quickly connect and transform all your sources so you can start focusing on getting the best insights.

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15. Stitch

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Stitch by Talend is a simple and extensible ETL that allows you to do more with the data you’re sending to warehouses with open-source connectors.

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16. Airbyte

Airbyte is an open-source ETL tool that offers wide extensibility so you can customize the setup to your resources and needs.

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Reverse ETL

A reverse ETL is just what it sounds like—instead of a tool that takes data from a source and makes it compatible for going into a warehouse, it copies data from the warehouse and writes it to a source. It gives operational nuance about what’s happening elsewhere when viewing information in a single source.

17. hightouch

Hightouch is a reverse ETL that operationalizes your data so you can leverage better insights—all with SQL.

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18. Census

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Census is an operational analytics platform that lets you send data from your warehouse straight into software as a service (SaaS) apps without needing help from engineering teams.

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Choosing the right data management tools for your stack depends on your needs

If your organization is serious about data, it needs to invest in the right data management tools. Although the tools you choose are ultimately dependent on your particular business needs, those listed above are highly recommended for most use cases. By aligning them as part of a modern data stack, you’ll enable better decision-making across your organization and pave the way for increased growth. 

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