IT organizations continue to devour data at unprecedented rates, and adoption and investment in business and data analytics tools are reaching new heights. To help analyze and store all this data, analytics solutions are benefiting from newer technologies including artificial intelligence (AI), machine learning, faster networks, and cloud computing.
But challenges remain when it comes to wider adoption of business and data analytics tools. For instance, a common problem occurs when a company finds that its data is not as clean or well-structured as anticipated, which presents problems for analytics solutions. Data integration is also a major issue, with data silos still existing across applications.
Figure 2 from our full report, Business and Data Analytics Adoption and Customer Experience, shows that the adoption rate for business and data analytics hit a high of 69% in 2021. Over the past four years, there has been a steady increase in both adoption and investment.
Business and data analytics refers to a broad range of tools to collect, store, integrate, analyze, and present information that supports decision-making. Our definition of this technology includes data warehouses, data marts, business intelligence, predictive analytics, data mining, dashboards, online analytical processing (OLAP), end-user report writers, and big data.
Real-time business analytics represents a newer class of tools designed to unearth the relationships among a range of data, use their own repositories, and often present themselves as easy-to-use tools with sophisticated graphical-presentation capabilities and responsive in-memory processing. One issue (or benefit, depending on one’s point of view) with these solutions is that line-of-business users can bypass the central IT organization and create their own departmental solutions.
“Most companies are collecting reams of data but are not making good use of it,” said Tom Dunlap, director of research for Computer Economics, a service of Avasant Research, based in Los Angeles. “It is crucial that analysts identify the data needed for decision-making and then present findings in an easy-to-understand way. Otherwise, the tremendous volume of data will frustrate decision-makers, who will be unable to make sense of it.”
The market is responding to the challenges. For instance, vendors specializing in data analytics as a service have touted new solutions for processing unstructured data. Moreover, the desire to better leverage data locked up in transactional systems, the falling cost of storage, and the emergence of easier-to-use business and data analytics tools are helping drive investment in these solutions.
Our full report examines the adoption trends for business and data analytics technology of all types, providing insight into how many organizations have the technology in place, how many are implementing it, and how many are expanding investments in new capabilities. We also recommend steps for a successful implementation.
To give additional insight, we look at the economic experience of those that have adopted the technology. We examine the ROI experience in terms of the percentage of organizations that report positive and break-even ROI within a two-year period. We also balance the potential ROI against the risks, measured in terms of the percentage of organizations that exceed budgets for total cost of ownership (TCO).
This Research Byte is a brief overview of our study, Business and Data Analytics Adoption and Customer Experience. The full report is available at no charge for subscribers, or it may be purchased by non-subscribers directly from our website (click for pricing).