David Menninger's Analyst Perspectives

Historical Databases: Becoming a Thing of the Past?

Posted by David Menninger on Aug 13, 2019 7:00:00 AM

Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected increase. Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. These seemingly ever-increasing volumes of devices and data streams offer both challenges and opportunities to capture information about a business and improve its operations.

To better understand how streaming data technology can be and is being deployed and used, Ventana Research is launching Dynamic Insights research on Streaming Data. The research will explore organizations’ experiences with streaming data initiatives and their attempts to align IT projects, resources and spending with new business objectives that demand real-time intelligence and event-driven architectures. Using concise web-based surveys, the Ventana Research Dynamic Insights platform gathers real-world data while immediately providing research participants with a personalized assessment of their organization’s efforts as well as research- and experience-based advice on potential next steps to improve. Each participant who completes the survey is provided insights to support decisions ranging from prioritizing applicationVentana_Research_Benchmark_Research_IoT_and_OI15_15_latency_in_IoT_applications_170111 and technology investments to what best practices are most relevant to the organization’s efforts.

The availability of real-time data is changing the way we live and the types of systems we build. Historical data stores, while still relevant, are becoming a thing of the “past,” meaning they will become repositories of data that was collected and processed in real time in the past and then stored. Streaming data is becoming the norm. Our Internet of Things benchmark research finds that nearly half (46%) of participants consider the processing of events in seconds or sub-seconds to be essential to their organization. Another fifth (21%) said they consider processing time measured in no more than minutes essential. The research also shows that more than nine in 10 organizations view speeding the flow of information to customers or consumers as crucial. Clearly it will become a competitive necessity to capture and utilize these streams of data more effectively.

However, many organizations are not ready to deal with real-time data. Fewer than one-third (31%) said they are fully satisfied with their ability to capture and correlate events today. Previous research suggests that lack of resources and inadequate experience and education are the most significant barriers in establishing a business case for deploying technology that can perform event or stream processing, detection and correlation. This new Dynamic Insights research will further explore reasons for this dissatisfaction.

Being able to process real-time event data efficiently and effectively creates opportunities for organizations to digitally transform themselves. In some cases, being able to use event data enables entire new business models, such as for ride-sharing businesses. In other cases, it can enhance the operations of established businesses with new opportunities and innovations, such as for the automobile industry’s connected-car initiatives. More than half (56%) of the participants in our Internet of Things research said they expect their event processing deployments to identify opportunities for improvement. And as organizations succeed with one initiative, they can leverage their platform to tackle additional opportunities.

The demand to capture and process event data is growing across both business and IT functions. As organizations increasingly process streams of event data, those that can tie all the streams together into a cohesive framework will be at an advantage: They will have a real-time view into operations across their organization, enabling them to react and respond more readily to market opportunities as they arise.

Click here to participate in this research, and here to learn more about Ventana Research’s methodology and large body of business research. Ventana Research also has conducted research in related areas including IoT, Data Preparation, Machine Learning, Data and Analytics in the Cloud, Next-Generation Predictive Analytics and Big Data Analytics and Integration.

Regards,
David Menninger
SVP & Research Director

Topics: business intelligence, embedded analytics, Analytics, Collaboration, Information Management, Internet of Things, Digital Technology, AI and Machine Learning

David Menninger

Written by David Menninger

David is responsible for the overall research direction of data, information and analytics technologies at Ventana Research covering major areas including Analytics, Big Data, Business Intelligence and Information Management along with the additional specific research categories including Information Applications, IT Performance Management, Location Intelligence, Operational Intelligence and IoT, and Data Science. David is also responsible for examining the role of cloud computing, collaboration and mobile technologies as they affect these areas. David brings to Ventana Research over twenty-five years of experience, through which he has marketed and brought to market some of the leading edge technologies for helping organizations analyze data to support a range of action-taking and decision-making processes. Prior to joining Ventana Research, David was the Head of Business Development & Strategy at Pivotal a division of EMC, VP of Marketing and Product Management at Vertica Systems, VP of Marketing and Product Management at Oracle, Applix, InforSense and IRI Software. David earned his MS in Business from Bentley University and a BS in Economics from University of Pennsylvania.