Top-4 iPaaS Considerations

Gil Trotino

Gil Trotino

Product Marketing Manager, K2View

Before choosing an Integration Platform as a Service (iPaaS), enterprises should take the following considerations into account.

Table of Contents

iPaaS Consideration 1: Know Your Options
iPaaS Consideration 2: Understand Your Needs
iPaaS Consideration 3: Examine your Organization
iPaaS Consideration 4: Data Fabric as a Service 

iPaaS Consideration 1: Know Your Options

There are multiple options to consider in the iPaaS domain, including:

  • Hosting options
    iPaaS is designed to operate on premises, in private or public clouds, or in hybrid environments. Each hosting option has its own requirements, in terms of data governance and data integration, as well as the management of updates and upgrades. Understanding which deployment options are supported by an iPaaS solution is critical.

  • Pricing models
    iPaaS offers different pricing and subscription models, including a fixed-fee or consumption-based pricing, which will vary according to features, data sources, and data volume. For example, enterprises with varying volumes of data traffic may find the on-demand (pay-as-you-go) model more cost effective.

  • Integration scenarios
    From real-time data exchange to enterprise-specific application integration, there are countless data integration scenarios to choose from. Different vendors focus on different target audiences, offering different capabilities to best suit their needs.



2: Understand Your Needs

Speaking of meeting specific needs, here are a few examples of factors enterprises should focus on:

  • Privacy and compliance
    Enterprises have specific demands, especially regarding privacy and compliance. The right iPaaS platform should be able to answer ever-changing regional regulations like GDPR, CCPA, and more. It should also be future-ready to address new laws or amendments, as they emerge.

  • Use cases
    What does an enterprise hope to achieve with its data? One of the most popular use cases is customer 360, for more effective data analytics, operational intelligence, and real-time decision-making. Others include data pipelining, test data management, and data privacy management.

  • Multiple sources and environments
    Today’s applications span multiple environments, both on premises, and in the cloud. So must your iPaaS solution. It should effortlessly and quickly integrate all sources with data endpoints, to ensure a single source of truth, and that the data is always available, fresh, and ready for pipelining.

The right iPaaS make cross-functional collaboration a reality.

  • Multiple teams
    Different departments across the enterprise need access to the data, some less tech-oriented than others. iPaaS must be a user-friendly, self-service solution that doesn’t require any expertise or training – which greatly reduces dependence on IT for data preparation and delivery.

  • Quick time to market
    Enterprises always need their data ready yesterday, so time to value is critical. When iPaaS is combined with approaches like shift-left testing, the result is more agile software development cycles, quicker time to market, and, ultimately, more satisfied customers.

  • Budget considerations
    We’ve mentioned different pricing models, and enterprises should make their iPaaS choice based on cost-effectiveness and ROI calculations. Anticipating future initiatives, such as company-wide cloud migration, is also wise because pricing may change, as your data volume grows.



3: Examine your Organization

  • Data structure and flow
    Organizing your data in a specific structure can impact your integration results you reach. For example, a data fabric based on business-driven data products enables enterprises to improve performance and enhance their data management capabilities. More on that, in Guideline 4.

  • Changing needs
    Today’s data management is defined by change. The number of data sources may grow, your chosen environment(s) may change, data volumes may fluctuate, and your reliance on microservices may increase. Picking a flexible platform, capable of adjusting on the fly, is essential.

46a-1A data product-based data fabric can be deployed in weeks.

  • Setup factors
    How long would it take to properly implement your iPaaS solution? How complex is the transition? Will multiple stakeholders need to be involved? If so, whom? Will you be able to incorporate data quality management best practices in the process? And the list goes on…



 4: Data Fabric as a Service 

Data Fabric as a Service (DFaaS) is quickly gaining ground among large enterprises. Here’s why:

  • Redefined data transformation
    DFaaS, the ultimate enterprise iPaaS, transforms all data, wherever it may be, into business-driven data products. The data products are originally defined and managed by specific business domains, but then later made available to all departments and data consumers throughout the enterprise.

  • Patented, disruptive technology
    Data products could be customers, products, suppliers, orders – or anything else that’s important to your business. Each individual data product is managed in its own secure Micro-Database™, continuously in sync with all source systems, and instantly available to everyone.

  • Data products you can trust
    A data product-based data fabric delivers a trusted, real-time view of all enterprise data. It deploys in weeks, scales linearly, and adapts to change on the fly. It supports modern data architectures such as data mesh, data hub, and multi-domain MDM – on premise, cloud, or in hybrid environments.

Learn more about what enterprises need to consider in an iPaaS solution.