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Data Management: Real-Time Data Analytics Stymied by Delayed Data Loading
Data is important, and as technology evolves there are continually new formats being introduced for best representing the content represented by the data.
Consider IoT data, streaming data from external sources, sensor data, graphs, key/value pairs, video/audio/image, objects, JSON documents and geospatial data. A survey by Intersystems and IDC found that most companies are interesting in managing data in these many different file formats.
One problem is that the legacy software used by many companies are unable to handle the many different file formats and transform and import tools are needed to capture the data. A second problem is that many businesses use methods like extract, transfer and load (ETL) and changed data capture (CDC) to transform and transfer this data to data warehouses and analytics packages, but because the transfer process is slow, often taking five days or more, real-time analytics is anything but real time.
This becomes a significant issue for companies that what to perform real-time data analytics. The survey found that three-quarters of businesses said that delay times for accessing data negatively impacts their business operations. 54 percent said that slow data acquisition limits their operational efficiencies.
