Strong relationship between optimising data pipelines and business value

Organizations are inundated with data, and many are struggling to maximize the value of that data since it’s flowing through unintegrated and leaky data pipelines. The research shows a direct relationship between creating stronger data-to-insights capabilities through data pipeline investments – ones that successfully deploy data management and analytics solutions to close pipeline gaps – to decision making that drives business outcomes.

• 86% of organizations in the top half of those surveyed with the best data analytics pipelines also get the highest decision-making scores
• 67% of organizations in the top half of those surveyed with the highest decision-making scores had the highest business outcomes scores

“Even in these challenging economic times, CEOs at major enterprises are continuing to invest in their data pipelines to close the gaps and enable their organizations with more high quality and valuable data for decisions,” said Dan Vesset, Group Vice President, Analytics and Information Management at IDC. “These leaders are increasing their enterprise intelligence quotient by automating the data preparation cycle through technology, giving employees the vital tools and time needed to analyze data for impactful insights that create real business value.”

Companies in the survey with the highest demonstrable data-to-insights capabilities, resulting in strong data pipelines that drive better decisions, see significant bottom line impact.

• 76% said operational efficiency improved by an average of 21%
• 75% said revenue increased by an average of 21%
• 74% said profit increased by an average of 22%

The challenges to deploying data pipelines that drive better decisions and business outcomes are significant. Organizations are dealing with complex and varied data types and sources, which can leak through data and analytics pipeline gaps. Of those surveyed, over 60% experienced significant challenges in assessing the value of data and identifying valuable data sources, often due to a lack of a data catalog. And over 42% surveyed identified assuring data correctness as a main challenge when processing or transforming data for analysis.

So even as organizations invest in techniques like machine learning and AI to enhance insight generation and analysis, it’s clear that the success of these investments is highly dependent on having an agile, automated and agnostic data pipeline that closes the gaps by working across any cloud, system and data source in real-time. Only by closing these gaps to eliminate data leaks can organizations transform their data pipelines to provide continuous and reliable enterprise-ready data that drives action and outcomes.

“Organizations must close the gaps in their leaky data pipelines to consistently transform their data into ongoing and real business value,” said James Fisher, Chief Product Officer at Qlik. “Our unique end-to-end approach to data integration and analytics gives organizations the ability to improve their data-to-insights capabilities at the speed of business for greater responsiveness and better outcomes.”