Evaluate Weigh the pros and cons of technologies, products and projects you are considering.

When data APIs go neglected, business intelligence suffers

Many businesses have mature API management practices in place for integration via REST APIs and application APIs. Unfortunately, those API strategies can create data silos for most business intelligence and analytics practices. That’s a problem that will only grow as demand for advanced analytics increases, according to industry experts.

Today, analytics pros face the challenge of programmatically answering questions using a limited data set available from an API. API strategies at most organizations have a singular function: to give application developers the ability to extend functionality of applications through process integration.

“These APIs often have limited surface areas and leave many of the data developer roles behind [without resources], because they lack rich query capabilities and are not designed for the purposes of data integration,” said Sumit Sarkar, chief data evangelist for Progress, an independent software vendor.

Data APIs in 2018

Sarkar has seen businesses with well-built data API practices successfully provide continuous operations and real-time capabilities. These functions strengthen analytics efficiency by provisioning data access specifically designed for data managers and business analysts, he said.

There have been encouraging developments in the area of data API management, Sarkar said. There are three in particular that stand out.

One of these developments is the IT industry’s adoption of OData, an industry standard RESTful data API. OData provides standard query capabilities and works without additional code to access data from popular analytical tools, especially those in data visualization, such as Tableau, Qlik or Microsoft’s Power BI.

A second development is better support for third-party analytics tools. SQL access is now increasingly published to developer portals for cloud applications, such as Microsoft Dynamics, NetSuite or ServiceNow.

Finally, as API management strategies continue to centralize authentication, authorization and business logic processes, there are more enterprise demands for SQL access to enterprise REST APIs. To that end, analytics tool vendors may release products that support REST APIs directly this year. However, they must first figure out how to accommodate the wide range of differences between REST APIs. This includes support for different security schemes, varying payloads, invocation methods and query capabilities.

Strategies for data APIs

Organizations should determine the requirements from all stakeholders as a first step in their API strategy planning, Sarkar explained. Teams also need to come to a consensus on the processes that govern access to analytics. For example, APIs that expose detailed data for the purposes of data discovery or compatibility should be provisioned with enterprise reporting tools, such as SAP Business Objects.

“Expect those [stakeholder] teams to ultimately become consumers of your APIs, even if there are no use cases today,” he said.

There are a few questions Sakar suggests teams ask when evaluating tools for managing data APIs. These include:

  • Can it work with existing API strategies?
  • Can it work together seamlessly with your existing security policies?
  • Can it support necessary operational integrations to scale?
  • Does it have support for open data standards such as Open Database Connectivity, Java Database Connectivity, and OData?

Sarkar predicts 2018 will bring a surge of interest among companies to merge management processes for app and data APIs.  He also predicted more collaboration between business intelligence and analytics teams and the API design teams. By year’s end, the distinction between application-oriented APIs and data APIs will be blurred, which will topple data silos.

Software Quality
Cloud Computing