Companies often fail to unleash the true value of their data due to poor data integration practices, which are the processes needed to move data between systems and applications to create value and effectively run operations. Fragmented data sources, inconsistent data formats, and congested data flows inhibit enterprise application effectiveness, cause delays and incomplete results with data warehousing, and create bottlenecks in operational processes.
Infoverity is an experienced partner for companies looking to implement high-quality data integrations to get the most out of their data and applications. Infoverity enables companies to simplify and unify their data ecosystem through the use of automation, which increases data transparency, the consistency of data flows, and data availability. Data integration allows companies to realize the full potential of their data. Ultimately, this results in streamlined business processes, improved decision-making, a reduction of manual tasks, and increased customer satisfaction.
Systems and applications do not always have seamless interface capabilities out-of-box, which hampers organizations’ ability to leverage data throughout the enterprise. Implementing data integration between systems allows everything to work together. It eliminates data structure conflicts and provides automated and accurate data between upstream and downstream applications.
Data must be updated in real time and available for decision-makers, end users, and applications. Automated data integration streamlines processes, ensuring employees’ time is spent on their jobs, not waiting for data. Automation also creates transparency and communication efficiencies between organizations and their customers and partners.
Ineffective data practices silo data, limiting who can use data to generate insights, as only a select few know what data is reliable or can extract data from systems. With data integration, companies experience data democratization, allowing non-technical users to harness data across every department in the business.
Without efficient data integration processes, companies experience cross-application latency, lack of visibility into data flow, and decreased ability to provide customers or users with real-time status feedback. This leads to customer dissatisfaction and internal distrust. With robust data integration, teams and customers receive accurate and timely data, alleviating these problems.
Gartner research shows that poor data quality destroys business value. A recent survey found that organizations believe poor data quality to be responsible for an average of $15 million per year in losses.
Data fragmentation improvement projects can deliver quick wins that help companies trim waste and manual work, according to Gartner. These efforts can cut annual data spend by 5 to 15 percent in the short term. Over the long term, businesses can nearly double that savings rate through quality data integration practices.
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