What is a Data Collaboration Platform?
by Brenna Dilger, on February 8, 2023
In today's fast-paced and data-driven world, organizations face an overwhelming amount of data, with information coming from a variety of sources and in many different formats. As a result, businesses are struggling to effectively access, integrate, and leverage this data to drive innovation and decision-making.
This fragmentation leads to a number of problems, including siloed data, inconsistent data quality, and difficulty in sharing data across teams and business partners. Furthermore, manual data management processes are time-consuming and error-prone, leading to missed opportunities and increased risk.
In a world where data is the lifeblood of many organizations, the inability to effectively collaborate with data can have serious consequences. The current state of data collaboration is in need of a solution that can bring order to the chaos, provide a centralized place for data management, and improve the ability of organizations and individuals to effectively use data to drive their decisions and achieve their goals. That's where a data collaboration platform comes in.
What is a data collaboration platform?
A data collaboration platform is software that simplifies, automates, and centralizes the collaboration and sharing of data assets. By centralizing data assets and providing automated self-service tools, these platforms make acquiring, distributing, and sharing data faster, easier, and more scalable than ever.
Understanding what a data collaboration platform does
So what exactly does a data collaboration platform do? It performs a few different functions that aid organizations in the acquisition and distribution of data:
A data collaboration platform makes data consistent and uniform, regardless of the source. Any data being shared by a distributor in its native format will be automatically formatted so that the acquirer can easily understand and use the data delivered to them.
With consistent data formatting, you can easily filter, combine, and package data from multiple sources. Organizations can find and acquire the precise datasets they need and leave out the datasets they don’t.
Data is automatically delivered to partners and clients at their preferred endpoint within hours.
Benefits of a data collaboration platform
A data collaboration platform allows organizations to seamlessly collaborate on data projects both internally and externally. With the increasing importance of data in today's business landscape, data collaboration platforms are a critical tool for organizations looking to optimize the value of their data assets and remain competitive in the data-driven economy.
Extract more value from data
Data collaboration platforms help organizations generate new and better insights by allowing teams to easily and seamlessly share and combine data from multiple sources. This enables teams to explore a multitude of connections and correlations between data sets, leading to exciting new discoveries and solutions.
By integrating external data sources, organizations can enhance the value of first-party data and make it more useful for decision making, product development, and other business initiatives. By sharing data internally through a centralized location, organizations ensure that all relevant data is taken into account when making decisions or working on projects, increasing efficiency and allowing teams to build on the work of others. These platforms also help organizations unlock the monetary value of their first-party data by making it easier to package and deliver data to partners and customers in a fast and secure manner.
Optimize costs and streamline operations
Data collaboration platforms automate the most complicated and time-consuming parts of data collaboration, significantly reducing the time and resources spent on data engineering and allowing laborers to focus on other critical tasks. This results in faster generation of insights, increased productivity, and more rapid revenue generation. Another one of the key benefits of data collaboration platforms is the ability to buy only what is needed, rather than the entire data "firehose." This not only saves organizations money but also eliminates the need for them to sift through unusable data since they are only paying for the data that is relevant to their specific needs.
In today's fast-paced business environment, organizations need to be able to quickly adapt to changes in order to remain competitive. Data collaboration platforms allow organizations to respond to changes in strategy or market conditions more quickly by providing almost instant access to the data they need. With on-demand data access, organizations no longer have to wait weeks or months for data to be converted and delivered to them, allowing for real-time decision-making and increased agility. Teams can easily access and analyze the data they need to inform their decision-making and adjust their strategies accordingly.
Data collaboration platforms provide organizations with a centralized data management and governance system, which helps to minimize security risks and meet compliance requirements. Centralizing data management allows organizations to ensure that data is properly protected and that access to sensitive information is controlled. This helps to minimize the risk of data breaches and other security incidents, and it ensures that the organization is meeting regulatory requirements for data privacy and protection. By implementing a centralized system, organizations can also ensure that data is consistent, accurate, and up-to-date. This leads to better data quality, improved data literacy, and reduces the risk of errors and inconsistencies.
Should you build or buy a data collaboration capability?
Some organizations are well equipped to run their data collaboration efforts in-house. For most companies, though, it can be more time-consuming, more expensive, and ultimately a lot less adaptable than using a data collaboration platform.
Questions to ask when considering build vs. buy
What available resources do you have?
For organizations with limited resources, developing and maintaining a data collaboration system can be a time-consuming, laborsome, and expensive process. On the other hand, using a data collaboration platform allows organizations to take advantage of automated processes, reducing the strain on their own resources.
What will the labor costs of developing and maintaining a data collaboration system be?
Developing and maintaining your own data collaboration solutions can require engineering teams, legal teams, and outsourced middlemen. The cost of labor for all of these hired teams can add up quickly. A data collaboration platform requires only payment for the platform and the price of the data you handpick to ingest.
What is the likelihood your data collaboration strategy will change in the future?
It can take months to find new data sources, test data quality, agree on terms, build pipelines between systems, and normalize and integrate data into your own systems. If you need to switch data providers, work with new data types, or send your data to a different endpoint, you’ll need to repeat a lot of this time- and labor-intensive work all over again. A data collaboration platform gives you scalability and optionality, so you can easily adapt your data collaboration strategy as your business strategy changes.
How do you find the right data collaboration platform?
Once you’ve decided to invest in a data collaboration platform, your next step is to find the right one for your business requirements. When making your decision, consider the following capabilities.
Your data collaboration platform should allow easy interoperability, or the ability to collaborate with multiple systems, platforms, and data formats. You’ll want a data collaboration platform that is able to automate the standardization of data assets to make transfers seamless, allowing the ingestion of data in any format and from any source.
Your data collaboration platform should provide an intuitive and easy-to-use interface that is accessible to non-technical users. It should be easy to point and click your way through the process of data sharing instead of requiring data engineering experts.
Your data collaboration platform should have the ability to easily integrate with other systems and platforms to exchange data. For instance, Narrative’s data collaboration platform has connectors built to Amazon S3, The Trade Desk, and Facebook, and provides a framework that makes it easy for Connectors to other endpoints to be built.
Your data collaboration platform should provide the assurance of having a pool of buyers and sellers for transactions. There should be a network of both buyers and sellers that are actively participating within the ecosystem.
Your data collaboration platform should allow you to tailor your data to specific needs and processes. It should be easy to create new custom datasets to distribute to your buyers or curate your own data acquisition order to meet your organization’s unique needs.
Your data collaboration platform should be able to handle large amounts of data and accommodate growing demands. It should be straightforward and simple to upload, organize, distribute, and acquire data in large capacities.
Your data collaboration platform should provide a streamlined and centralized vendor management process. Instead of having to finalize contracts and sign paperwork with every supplier you work with, you should be able to exchange data within the platform under one overarching standard agreement, minimizing administrative burden and allowing for faster data collaboration.
Your data collaboration platform should offer good value for its cost. With Narrative, you can operate in the cloud you’re already paying for. You’ll also have the ability to pay only for the data you acquire on a usage basis.
Security and privacy
Your data collaboration platform should provide absolute protection of sensitive data and give you the ability to control access and permissions to your data assets.
Compliance with regulations
Your data collaboration platform should fully comply with data privacy and protection regulations.
How other companies use data collaboration platforms
It can be helpful to learn how other companies use their data collaboration platforms and the results they get from those tools. Here is a list of a few companies that use a data collaboration platform to streamline data acquisition and distribution:
- How The Harris Poll builds addressable audiences with just IP addresses: Harris Poll uses a data collaboration platform to build addressable audiences for targeted advertising.
- How IdenX uses Narrative to quickly purchase numerous relevant data points: Idenx uses a data collaboration platform to cherry-pick relevant data from hundreds of billions of raw data points and from multiple suppliers at once.
- How Froyoo uses Narrative to scale identity graph creation: Froyo uses a data collaboration platform to link disparate identifiers into one comprehensive profile and centralize their data acquisition strategy.
Narrative is the world’s #1 data collaboration platform
Narrative provides everything you need to acquire, distribute, or share data. With Narrative's data collaboration platform, the most inefficient parts of data collaboration are automated so that you spend less time completing tedious backend work and more time gleaning insights, creating solutions, and driving revenue for your organization. Anyone within your company (even an intern) can point-and-click their way through a self-service process that gives them full control of their data.
With Narrative’s data collaboration platform, you have access to:
Automated data standardization
Using Rosetta Stone technology, data can be ingested in its native format from any source and be translated into a format that will be compatible with any system that acquires it.
Custom filters and controls
Slice and dice your first-party data into custom data products for your partners and clients or browse and select the exact data you want to ingest from multiple providers.
Fast and direct data delivery
Once data is selected for acquisition, it is automatically delivered to the acquirer at their preferred endpoint within hours.