Infogix Identifies Six Data Management Trends to Keep Your Eye on for 2020

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A new press release states, “Infogix, a leading provider of data management tools, today revealed its fourth annual list of trending challenges and opportunities in data management. ‘Twenty years ago, as Y2K loomed and people vacillated between anxiety and hysteria, there was angst that the markets would crash because of poor data,’ said Emily Washington. ‘Yet today, more data crosses the internet every second than was stored in the entire internet just 20 years ago. With that much reliance upon data, I believe that 2020 is the year that data quality becomes the epicenter of any data trend.’ Every year, Infogix’s global experts and influencers identify top data trends based on their decades of knowledge and experience working with clients worldwide. ‘As organizations continue to push the limits with data storage and processing, we see data quality as the underlying theme to ensure they’re leveraging data they can trust,’ said Washington. Below are the six trends Infogix has identified for 2020.”

The list begins, “(1) Real-Time Data to Disrupt the Future. Massive amounts of data are generated from a diverse set of industry domains, including social networks, e-commerce, transactions, IoT devices and web applications, requiring organizations to react quickly to extract value from that data. Traditional batch processing, where data is sent on a schedule from system to system, will not meet the demands of the changing data landscape. Companies are increasingly turning to event-driven architectures to handle growing volumes of streaming data. They are using distributed streaming platforms like Apache Kafka, ActiveMQ, Apache Pulsar, Amazon Kinesis and many others to provide high-throughput, low latency real-time streaming, flexible data retention, redundancy and scalability. In a world that demands lightning-fast speed-to-insights and real-time access to data, data quality has never been so important. Organizations must enlist vendors who can safeguard data quality to prevent data assets from becoming liabilities and provide validation at a speed and scale to match their data-in-motion.”

Read the rest of the list at PR Web.

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