The amount of data generated globally will double every 12 hours by 2025. With this much data moving through your organization, you’ll need to empower everyone, not just the data experts. Artificial intelligence (AI) will help help teams fish business insights from oceans of information, but to learn and improve decision-making, AI in turn requires data. That’s why we’ve created this glossary of data terms, so everyone in your organization – from senior leaders to individual practitioners – can become data literate now.
essential terms will help you and your teams, regardless of technical ability, feel confident talking about data and understanding how to use it to create business value.Batch processing
Batch processing is when a computer automatically runs a repetitive task or group of tasks on a large amount of data, processing it as a single unit rather than a series of separate jobs. Certain processor-intensive tasks can be inefficient to run individually; with batch processing, the data jobs are afghanistan phone number list run together, often at an off-peak time to conserve computer resources.
What it means for customers: When jobs like order processing are run as a batch, customers experience quicker turnaround times than when those tasks are handled individually, as well as more consistent and accurate results.
What it means for teams: Teams save time by minimizing the overhead required for individual tasks, and gain more consistent quality control by using standard business rules across a batch process.
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Business analytics
Business analytics is the practice of using data to test hypotheses and make predictions or more informed decisions, often around future performance. Business analytics is predictive, which means you model and analyze data to identify new insights and anticipate trends.