Market Trends

Buyers. Today, data buyers skew heavily toward the financial services industry, but that is changing as data science infiltrates most industries and companies. We suspect that most data buyers won’t start monetizing data products until they have experience launching and running an internal data marketplace. Most need to sort out legal and security issues before they feel comfortable externalizing internal data.

Sellers. Today, we see an explosion of data buyers seeking to cash in on the “data rush.” Most are building value-added data storefronts to attract and retain buyers using new data exchange platform technology. They use external data marketplaces, such as the Amazon Data Marketplace, as a marketing channel for their services. Their goal is to raise interest for their data products on an external data marketplace and then lure customers to their own storefront to make a purchase.

Operators. Data operators are launching data marketplaces to support a variety of public, private, and technology ecosystems. But not all will be successful. It can be challenging to achieve a “tipping point” with enough buyers and sellers to sustain a data marketplace. Some tech vendors are launching data marketplaces as a “checkbox requirement” to reassure prospective customers that they are on the cutting edge of technology.

Technology. It’s likely that we will see data catalog vendors morph into data marketplace exchange platforms. Data catalogs index metadata, which is great for curating and browsing data assets, but they are not actionable: users can’t directly access data from a data catalog. Data marketplaces provide a mechanism to turn data catalogs into a data provisioning system which will turbocharge usage. Some data catalog vendors have already introduced data provisioning features or data marketplace companion products (see Informatica below) and we expect this trend to continue.

It’s likely that we will see data catalog vendors morph into data marketplace exchange platforms.

Market Trends Driving Buyers, Sellers, and Operators

Buyer Pain Points

Problems Acquiring External Data: Finding data, evaluating data, poor data quality, lack of lineage, aggregated (not atomic) data, non-compliant data, inflexible licensing, dealing with schema changes, securing connections, configuring APIs, cleaning & transforming data, joining data sets w/ common IDs, and maintaining data pipelines.

Problems Integrating External Data: Dealing with schema changes, securing connections, configuring APIs, cleaning & transforming data, joining data sets w/ common IDs, and maintaining data pipelines