Enable Data Democratization and Self-Service With a Data Marketplace

Last Published: Aug 09, 2022 |
Jitesh Ghai
Jitesh Ghai

Chief Product Officer

data democratization

To do their jobs well, people across an organization need quick and easy access to data they can trust. By providing that access, CDOs enable organizations to identify new opportunities, introduce operational efficiencies, and build new products and services to grow revenue. But many of the people needing access lack technical skills. So, how can you deliver that data in a user-friendly way—and also ensure that it’s clean and prepared and trusted? Create a data marketplace that makes the process as simple as shopping online for your favorite shampoo.

As we described in a previous post, a data marketplace, just like popular sites like Amazon.com, enables consumers to browse for the data they need using a familiar shopping experience. By building a new self-service model that supports data democratization, you can empower teams across your organization—from the executive suite to marketing to manufacturing—to drive productivity, efficiency, and the effective use of data.

Six Key Steps to Building a Data Governance Foundation

How to start? You can’t simply share all the data within your organization—that would result in chaos. Instead, you need to use a governed framework to ensure that data can be effectively accessed, discovered, browsed, shopped for, and delivered, similar to the way Amazon vets suppliers before they’re allowed to publish their products on Amazon.com.

Figure1: A strong governance foundation is key to creating a self-service data marketplace.

To create a functioning marketplace, you need to consider the backend services that ensure data is delivered when you want it. These six steps are essential to building a foundation for governed data democratization:

  • Define data standards for things like terminology, quality, privacy, and use
  • Discover the sources and data fields where the standards should be applied
  • Execute standards to cleanse and enrich
  • Ensure the consistency of master data across on-premises and multi-cloud applications
  • Enforce protection and privacy standards of data at rest and in motion
  • Compliantly deliver data to all employees for analytical and operational use cases

With this foundation, you can make data sharing productive, providing data consumers with sufficient context about the quality, criticality, purpose, and use of data within your organization.

Scaling With Intelligence and Automation

The size, complexity, and distributed nature of data, combined with increasing requirements for continuous intelligence and speed of action, mean the manual data governance and management practices of the past can never keep up with the agile business needs of the future. The underlying technology foundation described above requires AI-powered automation to scale. Some examples of how Informatica’s AI and machine-learning capabilities known as CLAIRE can help you increase productivity and reduce costs with automation include:

  • Data governance – Automate the association of policies and rules with data elements
  • Data discovery and cataloging – Automate data discovery, cataloging, and the association of business terms to technical metadata
  • Data cleansing and quality – Automate the profiling of data and execute data quality rules
  • Data mastering – Automate the classification of product master data and the association of standardized descriptions
  • Data privacy and protection – Automate the linking of structured and unstructured data and the creation of a subject registry index
  • Data delivery – Automate the transfer of data to reporting tools and analytical data stores

Auto-curation capabilities are an essential part of Axon Data Marketplace, the industry’s only intelligent, integrated, enterprise-scale governed data marketplace. The Axon Data Marketplace enables your organization to create data sets, ensure the appropriate quality and privacy standards are documented against those data sets for their “fit-for-purpose” use, and publish them within the appropriate categories to make them shoppable.

Making Data Shopping User-Friendly

Data consumers enjoy a simple shopping experience similar to that of Amazon.com, except that now they’re browsing for a data set and looking at data quality scores and privacy policies associated with that data set to get the context of the quality and trustworthiness of the data. They can also see how complete the data is, whether they can access it, and how sensitive the information in the data set is. Once they’ve discovered these data sets, they can simply add them to our shopping cart and check out.

The checkout experience initiates a triggered workflow, which can be an integration with existing processes within your organization through Jira, ServiceNow, or our workflow capabilities to authorize the approval of consumption for a given shopper.

Once authorized, we’re able to fulfill the order by leveraging our metadata intelligence, because we’ve scanned and know the structure of the various data sources. And because the data set defines what the final structure will look like, we can automatically generate our integration mappings and provision the necessary integration job and the ultimate data set to where you’d like to analyze that data.

Providing an End-to-End Experience

The Axon Data Marketplace provides an end-to-end experience for data suppliers to intelligently and automatically scale, build, and onboard data sets. This makes it easy for data consumers to quickly shop for and discover data, understand the context of data, and effectively receive data once they’re authorized to consume it.By leveraging an intelligent, integrated, enterprise-scale data marketplace, you can help teams work more efficiently, drive innovation, and generate new revenue streams.

See how the Axon Data Marketplace can enable a frictionless data shopping experience for your enterprise with our on-demand webinar, “Unleash the Power of Creating Value with Trusted Information.” Watch now.


First Published: May 04, 2020