Business leaders are growing weary of making further investments in business intelligence (BI) and big data analytics. Beyond the challenging technical components of data-driven projects, BI and analytics services have yet to live up to the hype.

Early adopters and proponents were quick to frame solutions as miraculous reservoirs of insight and functionality. However, big data has not met many C-level executives’ expectations. This disconnect has many executives delaying projects, filing end-to-end big data solutions under “perhaps, in the future.”

Increasing interest and investment in distributed computing, AI, machine learning and IoT are generating practical and user-friendly tools for ingesting, storing, processing, analyzing and visualizing data. Still, the necessary IT, data-science and development operations are time-consuming and often entail large resource displacements.

This is where data pipelines are uniquely fit to save the day. The data pipeline is an ideal mix of software technologies that automate the management, analysis and visualization of data from multiple sources, making it available for strategic use.

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