Five Reasons Why Modern Data-Driven Organizations Need a Foundation of Predictive Data Intelligence

Last Published: Jun 17, 2022 |
Dharma Kuthanur
Dharma Kuthanur

Vice President, Product Marketing

By now, we all understand that digital transformation is really data-driven business transformation. So it’s no surprise the organizations that have successfully moved forward on their digital transformation initiatives are also the ones that have effectively brought people and data together. These organizations recognize the importance of empowering data users in their organization to easily find, understand, trust and access the data they need for analytics, AI and, more broadly, data-driven decision making. But when it comes to putting this into practice, we are seeing a different story: a gap between aspiration and reality. A recent Data Trust survey conducted by IDC indicated that 83% of executives have articulated the need to be more data driven compared to before the pandemic, but only 30% of practitioners say actions are driven by data analysis.1

Organizations understand that data intelligence — contextual understanding of data enabled by metadata-driven insights into data classification, quality, lineage, ownership, usage and relationships — can play a critical role in addressing this challenge. However, many existing solutions for data intelligence are failing to live up to expectations. Stewart Bond, Research Director at IDC, succinctly summarized this in a recent presentation when he stated that “Intelligence about data is expected but NOT being delivered.”2 Although there are many reasons why they are falling short, a common theme we have observed is that most of these data intelligence solutions are not linked to data delivery. And when that is the case, data intelligence is not actionable; it remains disconnected metadata, relying on cumbersome manual workflows to drive actions. As a result, these data intelligence solutions:

  • Do NOT deliver quick value with predictive recommendations for data users
  • Do NOT empower data consumers to engage with data
  • Do NOT enable tangible business outcomes

What is needed to get past these challenges? As the pace of digital transformation accelerates, organizations realize that the costs of getting left behind are becoming greater. Getting timely value from data intelligence is becoming ever more critical — they cannot afford to wait months and years to start seeing this value. Driving business outcomes and value from data also requires them to enable data consumers for quick and easy self-service access to trusted data. After all, what’s the point of having lots of data and metadata about the data if you cannot put the data in the hands of data consumers when and where it’s needed? Finally, lest we forget, they have to scale this across the organization, for all enterprise data, and do that without overwhelming their data management and data engineering teams.

The bottom line is organizations need the ability to unlock exponential value from their data. Doing this at scale requires the following critical capabilities:

  1. Unlock immediate data value with predictive recommendations and automation powered by metadata intelligence from the organization AND beyond
  2. Empower data consumers and drive business outcomes with a self-service data shopping experience that’s linked to automated data delivery
  3. Fully understand their data with connected metadata, context and insight across the data value chain for all enterprise data — any data source, any data type, any cloud
  4. Enable inherent trust in their data with unified governance, catalog, quality and marketplace capabilities
  5. Grow and scale as their business needs evolve with intelligent, modular, cloud-native services powered by elastic and serverless execution

In effect, what’s required is a single, unified solution for predictive data intelligence in the cloud with integrated governance, catalog, quality and marketplace capabilities, powered by broad and deep cloud-native metadata intelligence. A solution that will provide modern data-driven organizations the data foundation that they need to:

  • Accelerate and automate data governance to deliver trusted data
  • Enable data sharing programs that empower data consumers to engage with data
  • Drive analytics and business outcomes with trusted data

To learn more about how Informatica delivers predictive data intelligence that leverages the cloud-native capabilities in its Intelligent Data Management Cloud (IDMC) platform powered by its metadata-driven AI engine, CLAIRETM, join us for these upcoming webinars:
Meet the Experts: Innovations in Cloud Data Quality
Meet the Experts: Empowering Business with Cloud Data Governance & Catalog
Meet the Experts: Fostering Data Sharing with Cloud Data Marketplace

1 Data Culture Survey, IDC December 2020, N=455, Data Trust Survey, IDC December 2021 N=500
2 Source: “In Data We Trust. Or Do We?” Stewart Bond, IDC Directions Conference, March 2022


First Published: Jun 17, 2022