Insights-as-a-Service: Making the Most of Big Data and Analytics

by January 13, 2021 0 comments

Insights-as-a-Service

How leveraging insights-as-a-service can expedite business value?

Today, we are bombarded with a continuous flow of big data sets. Such data sets carry information in both unstructured and structured forms. To derive meaning from the data can be challenging but it holds significant promises to drive business growth. This is where enterprises demand advanced big data and analytics tools to process vast amounts of data they collect. Insights-as-a-Service is an emerging concept in analytics that leverages predictive analytics and business intelligence to offer effective action plans from data warehouses.

Insights-as-a-service not only derives information from data but also finds other data sources to answer specific business questions. It addresses and provides solutions to data processing challenges through in-depth analytics on the cloud. It also enables companies to cut their costs significantly by confiscating the need for data professionals and the complex infrastructure required to run analytics on-premise.

 

Evolution of Insights-as-a-Service (IaaS)

Undoubtedly, data is the new oil for today’s businesses to fuel their growth. Owing to the surging amount of data on a daily basis, companies face a growing set of challenges to exploit and excerpt actionable insight from their data. The advent of Insights-as-a-Service introduces a cloud-enabled interaction for companies and provides them with insights and business intelligence. It also helps in providing crucial steps required to leverage such insights towards accomplishing business goals.

Most businesses today find themselves in intricacy while processing voluminous data. They face challenges in determining which data they require most to meet their goals and what additional data they may need. In this context, IaaS can be an obvious solution, providing companies with sourced data that can help support the business case looking to be solved.

The integration of insights-as-a-service will likely grow in businesses in the coming days as companies already trust the cloud more than ever as a model for offloading their most critical operations. Furthermore, IaaS can aid in increasing data prioritization from what is collected. Eventually, companies will be able to build a plan for measuring whether they are making the best use of their data, how they glean it, and what they expect more from this as-a-service business model.

 

Why Insights-as-a-Service?

Big data has become an overused business buzzword today. But it often doesn’t mean that all the data businesses capture and store have value. As data requires a cycle of analysis to extract value, most companies lack the tools and human resources essential to scrutinize the data they gather and turn it into an analytics model. According to an IBM report, Generation D businesses that are sufficiently data-rich and analytically-driven, understand the uniqueness and value of data and analytics and know how to coalesce that with cloud, social, and mobile technologies. These businesses were found to be three times more likely to excel at developing insights regarding their customers and the marketplace.

Considering a market report, the Insights-as-a-Service market is forecast to value at US$3.33 billion by 2021, growing from US$1.16 billion in 2016 at a CAGR of 23.5 percent. This market surge is largely driven by the augmented need for customer management. Integrating cloud-based CRM tools can draw the relationship between perception and satisfaction, and commitment and loyalty that underline the significance in various industries. As better customer response can help organizations understand their requirement and come up with satisfied solutions, this has led to the demand for IaaS.

An IaaS platform can enable companies to create a unified dataset that can easily be scanned and queried for better insights. It helps collect data, refine and predict it and derive meaningful insights.

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