Data Consistency Coin Toss: Survey Reveals Enterprises Gamble on Customer Satisfaction
Nearly 45 percent of organizations would move ahead with a design approach that may not guarantee consistent results to accelerate time-to-market.
Join the DZone community and get the full member experience.Join For Free
VoltDB, the only database purpose-built for fast data applications, today announced the results of a new survey examining the attitudes, perceptions and realities of transactional data consistency for today's enterprise leaders and developers. The survey, conducted by independent panel research firm Research Now, uncovers the state of transactional consistency in the enterprise and which customer experience compromises organizations are willing to make for faster product and solution deployments.
The survey found that nearly 70 percent of IT decision makers and developers agree that reliable database transactions and database consistency are most important to customer-facing operations, with 60 percent saying it would improve customer satisfaction. In fact, nearly 40 percent of respondents are more afraid of learning about an app's inconsistency issues and/or data reliability issues from an angry customer than they are of finding out from their boss or others within their organizations. Despite the importance of customer-facing operations, only 58 percent of organizations consider having reliable transactions critically important to their business.
- Only half of organizations (53 percent) believe the most important part of their operational business applications is that they use immediately consistent and accurate data.
- Still, businesses acknowledge that applying inconsistent data to business analytics risks serious customer service and satisfaction issues (62 percent), negative impact on the brand (53 percent) and financial loss (47 percent).
- Respondents report that unreliable customer transaction data would both impact future customer interactions (51 percent) and could negatively impact customer retention altogether (36 percent).
- Nearly 75 percent of respondents say data consistency is the top priority over speed/time to market (21 percent) for their organization – despite 45 percent saying they would move forward with a design approach that could not guarantee consistent results to accelerate time to market.
- Although 43 percent of respondents say their operations are dependent on reliable transactions and consistent data all of the time, only seven percent of operations are actually conducted with consistent and accurate data all of the time.
- While 95 percent of respondents say they are taking action to ensure data consistenc and accuracy, 64 percent say they rely on the application developer to do so – leaving room for human error.
"We had experienced something curious in some of our customer meetings over the past few months. Some customers, like those in telco and financial services, seemed to really understand the value of consistency, while prospects in some other industries like adtech and media didn't, so we commissioned a survey around the topic of data consistency. We saw a widespread misunderstanding of what ACID means, what benefits consistency provides and what the term 'transaction' really means," said Dennis Duckworth, Director of Product Marketing at VoltDB. "A true transaction is a grouping of operations as a single unit of work that allows a data management platform to remain accurate, meaningful and reliable despite all its users doing all sorts of bizarre things to the data, all at the same time. It is the reliability component that is often overlooked, but in a world of real-time interactions, enterprises cannot afford 'eventual consistency;' they need data that is fast and delivers consistent results time and again. True transactions are critical for consistency."
You can download the data visualization further outlining the findings of the study at: https://www.voltdb.com/data-consistency-vs-consumer-impact
Opinions expressed by DZone contributors are their own.
MLOps: Definition, Importance, and Implementation
You’ve Got Mail… and It’s a SPAM!
What Is JHipster?
Testing Applications With JPA Buddy and Testcontainers