Table of Contents In today's globalized economy, businesses of all sizes rely on seamless data exchange with their partners, suppliers, and customers. For decades, Electronic Data Interchange (EDI) has been the backbone of this communication, enabling companies to automate the exchange of important business documents such as purchase orders, invoices, and shipping notices.

Table of Contents In today's fast-paced digital landscape, marketing teams are under immense pressure to deliver personalized, relevant campaigns that drive results. But how can businesses ensure that their marketing strategies are effective? The answer lies in marketing analytics—the process of analyzing marketing data to measure performance, optimize strategies, and ultimately boost ROI.

Table of Contents Secure File Transfer Protocol (SFTP) has become an indispensable tool for organizations needing to securely move files between systems. With its robust encryption and reliability, SFTP ensures sensitive data is transferred in a way that meets modern security standards.

Bigtable provides the query latency that real-time systems need when using data from BigQuery via the EXPORT DATA to Bigtable (reverse ETL) function.

The BigQuery tables for Apache Iceberg storage engine offers autonomous storage optimizations, clustering, and high-throughput streaming ingestion.

Many enterprises face significant challenges when it comes to building data pipelines in AWS, particularly around data ingestion. As data from diverse sources continues to grow exponentially, managing and processing it efficiently in AWS is critical. Without these capabilities, it’s harder to analyze and get any meaning from your data.

Pharmaceutical industry leaders are adopting new artificial intelligence (AI) technologies and increasing process efficiency. The Infosys report on AI adoption shows that pharmaceuticals are among the most mature industries in Al adoption. In the same report, 40 percent of the respondents claimed their organizations had deployed Al and that it was working as expected. AI-powered features help them manage massive volumes of pharmaceutical data with great accuracy and speed.

Alright, I’m back. Time for part 2. In the first part, I covered how we handle bad data in batch processing. In particular, cutting out the bad data, replacing it, and running it again. But this strategy doesn’t work for immutable event streams as they are, well, immutable. You can’t cut out and replace bad data like you would in batch processed data sets.

Let’s say you’re leading a company that receives thousands of documents daily. These documents come in various formats like Excel, PDFs, CSVs, and more. And they differ in terms of layout. Before you can analyze the data, your team spends hours sorting, cleaning, and preparing these documents. Most of their time is spent preparing the documents for integration into business systems. Then, a colleague shares how intelligent document processing helped him save time and boost productivity.