Data’s emergence fuels a resurgence for the business analytics crowd

As data analytics takes its place at the heart of corporate strategic planning and daily operational execution, traditional business analytics companies are cleaning up, according to research by industry analyst Ovum.

Most of the leaders in the sector — whom Ovum identifies as IBM, Oracle, SAP and SAS — are achieving double-digit revenue. Furthermore, it’s the quality of the growth that stands out — coming from new license revenues rather than maintenance and services.

According to the report, enterprises need to shift the basis of differentiation to focus on smarter and more efficient use of data. The authors argue that this means the ability to extract, integrate, analyse, and interpret data related to the business in a timely, proactive way should become one priority for business intelligence (BI) vendors.

BI vendors today cannot be choosy about the data they analyse. Unstructured and semi-structured data is more relevant for BI today than ever before, and so is invaluable customer and pipeline data sitting idle in CRM systems. Vendors that fail to see the forest for the trees (curated data) will lose business and hinder growth for their customers,” writes Surya Mukherjee, Senior Analyst at Ovum.

Visual data discovery solutions have emerged as one of the most important developments in the BI market during the last couple of years, write the authors. And they attribute the uptake to the ease with which users can source, mash up, analyse, and visualise well-defined data with intuitive and visually driven solutions, often with little to no help from IT.

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Data creation, preparation, and consumption are now merging into one activity. Enterprises expect vendors to automate data mapping to the extent that data created or updated in one system should reflect immediately in others. This requires a greater focus on data management technologies, but without the encumbrances of long, drawn-out, IT-driven deployments. Business should be the driving force for data,” wrote Mukherjee.

Ovum argues that nearly half of BI and analytic applications built and run in 2014 will integrate, to some degree, text and data analysis and modeling, complex business rules, and predictive analytics. That, in turn, will mean that companies need to crunch more data and run more sophisticated analytics, driving a demand for more processing power to maintain acceptable response times. “Enterprises today need BI that is smarter and faster, but invisible. User interfaces and experiences that are reminiscent of the enterprise resource planning era will not survive the next five years.

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