In the Big Data era, organizations across all industries and sectors are accumulating huge amounts of qualitative data in search of patterns and insights that can be used to guide corporate decisions and policies. Many such initiatives are being stymied by inadequate data analysis capabilities, however.
Although 94 percent of organizations believe data analytics is important to their business growth, most have not invested enough in the technology and talent needed to effectively utilize their data resources, according to the “2020 Global State of Enterprise Analytics” study conducted by the market research firm Hall & Partners.
The survey of 500 business intelligence and analytics professionals found that most line-of-business employees are “data deprived” because they don’t have access to self-service data analytics tools. Without those tools, 79 percent say they have to ask IT staff for help analyzing data sets. As a result, they say, it takes hours or days to get the information they need, damaging their ability to make informed business decisions in a timely fashion.
Such delays often translate to lost business and missed opportunities. Other studies suggest that U.S. business are losing nearly $10 million each year due to poor data analysis capabilities. Meanwhile, employees in some industries waste as much as 50 percent of their time each week trying to find data they need.
Inside the Numbers
Without analytics, big data is just a bunch of numbers. To gain the full advantage of data resources, organizations need to invest in self-service tools that democratize analytics.
Conventional business intelligence and data aggregation solutions usually require an analytics expert to run database queries. To gain data-driven insights at business speed, organizations need self-service analytics that cut out the middleman and allow end-users to access and use data analysis in their day-to-day work.
The Harvard Business Review Analytic Services found that organizations enjoyed improved financial performance from their analytics if those tools were widely distributed across the organization. More widespread use of analytics also increased productivity, reduced risks and helped individuals make faster and better decisions. In data-driven companies, employees become more proactive and creative, generating a flow of new ideas. Managers use analytics to test those ideas, deliver feedback and encourage collaboration and innovation.
Converge’s Advanced Analytics
With our advanced analytics solutions, Converge can help customers enhance data-driven decision-making throughout the organization. Working closely with our vendor partners, we can design and implement solutions that leverage a variety of AI-powered techniques such as deep learning and natural language processing, as well as blockchain technology for ensuring data integrity.
Many of our customers have had great results with IBM Cognos Analytics, a state-of-the-art self-service analytics platform. It has many AI-infused features that help users quickly discover hidden insights, recommend visualizations and make conversation in natural language.
One of the best characteristics of IBM Cognos Analytics is that it accommodates users of all skill levels. The platform’s Knowledge Discovery Service can be set for either deep or shallow mode, depending on the level of detail required and the user’s expertise. In deep mode, it conducts a several types of analysis to capture data characteristics and relationships. Shallow mode is much faster because it analyzes metadata only for more generalized evaluation.
To create a truly data-driven environment, organizations must have the tools to examine vast stores of data for qualitative information that will enhance the decision-making process. Furthermore, those tools should be available to everyone from executives to front-line workers to help drive faster and more insightful decision making. Give us a call to learn how we can help you improve your data analytics capabilities.
