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Documentation forms an integral part of operations in almost every industry. Take logistics and transportation, for example, where companies process hundreds of thousands of documents daily to keep the goods in motion and the supply chain functional. So, what are logistics companies doing to handle such a vast number of documents? More importantly, how can they use the intelligent document processing (IDP) technology to manage their documents and extract the data they need?

Businesses across various sectors want to leverage AI to increase efficiency, reduce cost, enhance customer experience, or do all that in one go. The mortgage industry is feeling it, too, thanks to the several potential areas where AI technologies can impact. For instance, AI can help mortgage lenders by: In fact, according to a Fannie Mae survey, mortgage lenders believe compliance, underwriting, and property valuation are all ripe for AI integration.

For many organizations, Workday is a core system housing vital data on HR, payroll, finance, and more. However, extracting and utilizing that data for analysis can be a challenge. The new Simba Workday ODBC and JDBC Drivers simplify this process, enabling seamless access to Workday data through standard database interfaces. With Simba Drivers, you can effortlessly integrate Workday data into your analytics tools, ETL workflows, or custom applications, unlocking its full potential for decision-making.

Many enterprises have heterogeneous data platforms and technology stacks across different business units or data domains. For decades, they have been struggling with scale, speed, and correctness required to derive timely, meaningful, and actionable insights from vast and diverse big data environments. Despite various architectural patterns and paradigms, they still end up with perpetual “data puddles” and silos in many non-interoperable data formats.

As organizations adopt a cloud-first infrastructure strategy, they must weigh a number of factors to determine whether or not a workload belongs in the cloud. Cost has been a key consideration in public cloud adoption from the start. Today, energy efficiency is gaining importance, not only for cutting costs but also as a vital step toward sustainable business practices. By optimizing energy consumption, companies can significantly reduce the cost of their infrastructure.

A big part of data teams’ responsibilities is dealing with the unpredictable. Data pipelines don’t always run without incident: you need to rerun processes and fix data processing issues—in other words, put out data fires—to keep stakeholders happy. For every significant roadblock, additional time and effort is given over to investigation and post-mortem reports to make sure the incident doesn’t reoccur. But naturally, they keep happening.