Data aggregation is the process of combining and summarizing data from disparate sources into a cohesive dataset. It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Then, you can leverage it to gain a holistic perspective on your operations and market trends, design effective risk management practices, and make more informed decisions overall.

Time series data is everywhere. It captures how systems, behaviors and processes change over time. Enterprises across industries, such as Internet of Things (IoT), financial services, manufacturing and more, use this data to drive business and operational decisions. When using time series data to perform analytics and drive decisions, it’s often necessary to join several data sets.

Learn why SAP data is the critical ingredient for manufacturing organizations to move from reactive to predictive analytics.

A part of Gemini in BigQuery, data insights leverages table metadata and profiling information from Dataplex to surface relevant, executable queries.

There's no doubt that, as a technology provider/integrator, you're likely seeing many customers across all segments looking to advanced analytics and artificial intelligence for optimizing their growth. Given the vast volume of data that these innovations consume or create, it's clear to see the importance of being able to offer your customers reliable, secure, sustainable and scalable data infrastructure solutions.

It's hardly groundbreaking to mention the importance of data privacy in the digital world and in business…it's a topic we've previously explored. However, acknowledging its significance is one thing, implementing actionable steps is another. This realization is the inspiration behind this article. There’s no need for you to jot anything down or replicate the checklist, as we’ve prepared a downloadable gated version ready at the conclusion of this article. So let’s get into it.

How to build a flexible pipeline to output Cloud SQL for SQL Server audit records to internal or external sinks with minimal coding in Cloud Data Fusion.