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Bridging the Data Divide: Getting the Most Value From Data With Integration

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Today’s enterprises “can no longer afford to wait for the presentation of analytical results in order to optimize operations,” agreed Steven Noels, CTO of NGDATA. “In a time when context and behavioral data is readily available in real time, competition is going to be won by the companies that are able to decide on the most relevant actions the closest to the moment of the greatest possible impact. The data is already there, now it is a matter of acting upon it.”

Prepare for a Data Deluge From the Internet of Things

The emerging IoT is adding a vast new dimension to the challenge of data integration. “IoT devices are disrupting our world with wearable technology, connected cars and homes, even connected cities,” said Luis Benavides, CEO of Day1 Solutions. “The implications are huge. IoT will only exacerbate issues related to data traffic. Throw in the hybrid cloud environment and you have this increase of management between the private and public cloud.” Experts agree this is both a challenge, as well as a tremendous opportunity to build businesses on data. “The combination of smart devices, the cloud, and big data has created a massive business opportunity at the intersection of the super-connected consumer and the rapid spread of smart devices,” said Rowlands.

Emphasize Self-Service

While industry experts encourage greater automation and machine learning to rapidly assemble information, it’s also critical that end users be able to assemble insights quickly and easily as well. “Connectivity is the new integration,” said Sumit Sarkar, chief data evangelist at Progress. The most important step toward data integration is “getting data integration into more people’s hands,” he said, adding that the democratization of data integration is through direct connectivity. Line-of-business professionals—citizen developers and integrators—“are demanding self-service point-and-click integration patterns to external data from SaaS applications and analytics platforms. This allows users to integrate data from many sources and to view that integrated data from a number of angles to discover insight and actionable results.”The democratization of data is an important competitive consideration as well. “Everyone must be able to access and interpret real-time information in order to stay in front of customer trends and competitive market shifts,” said Sarig. “This requires new technology and a fresh approach that provides more than advanced reporting or fancy visualizations —which are just the tip of the iceberg.”

With big data visualization come big challenges to integration, especially when it comes to delivering to the front end. “It’s important to consider the challenge that moving potentially large amounts of data imposes in terms of execution time and overall security, and select a solution that can perform these operations in situ,” said Flavio Villanustre, vice president of technology at LexisNexis Risk Solutions. “A platform that provides integrated visualization is also of benefit since exploratory data analysis depends on adequate visual analysis to understand the characteristics and semantics of the data.”

Expand on Metadata

Data integration experts stress the expansion and refinement of metadata as being key to the data integration process. It’s “more and more critical that data managers ensure they have ways to collect metadata, which provides context and meaning for every piece of data collected,” said Rowlands. “Being able to provide credible traceability for the information used to operate the business just keeps getting more vital. Most organizations have silos of data management—it all needs pulling together so that every aspect of a data asset is instantly visible to support agile reaction to changing opportunities.”

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