Working with big data and analytics is becoming increasingly necessary for companies attempting to generate actionable insights from massive structured and unstructured data sets. The ability for a company to gain business insights through data will certainly prove to have a competitive edge.
However, mining diverse and complex data without a flexible and scalable platform can be very challenging. This has been one of the driving factors for “Insights as a Service” (IaaS) gaining momentum, particularly with the increasing interest in artificial intelligence (AI).
At present, the market is driven by the need for businesses to mine a large amount of structured and unstructured data and gain insights and intelligence to enable data-driven decisions for achieving desired business outcomes.
This is driving many firms to experiment with concepts such as third-party insight exchanges and virtualized data science labs to make AI accessible across the enterprise as a service. This model allows a user to request the optimum information necessary to drive business intelligence.
IaaS can accelerate experimentation by meeting needs for:
A foundational platform
Data-science-models tailored to business need
IaaS platforms address the need for in-depth analytics on the cloud and provide solutions to unique data-specific challenges. Moreover, they allow companies to reduce their costs significantly by removing the need for data scientists and the complex infrastructure required to run analytics on-site.
They provide a visually appealing and comprehensive data set that helps optimize operations and enhance revenues; merge both internal and third-party data sets, and use AI to efficiently scan these sets quickly.
IaaS platforms let companies create a unified data set that is easily scanned and queried for better insights as opposed to fragmenting data. Combined with AI and machine learning algorithms, IaaS also expedites the ability to obtain insights and act on them.
As we experience a paradigm shift towards the data-centered future, where IaaS services become a precursor to insightful solutions, the question to ask is whether your organization is working on actionable insights or are you lagging behind!