Report: Observability More Important Than Ever
Only a small number of companies currently have mature observation processes in place, making it a field ripe for innovation.
Topic: Big Data
Big Data technologies and use cases for real-time analytics. Big Data technologies, market insights, and use cases for real-time analytics.
Breaking Down Data Silos with Automated Integration
Automated integration takes much of the burden off of the technical staff by handling the numerous manual tasks required to make siloed data available to …
A Call for End-to-End Data Analytics Supply Chains
The concept of an end-to-end data analytics chain is already proving itself in business settings, with leaders reaping substantial
Integration Needs Scalability, User-Friendly Interface
Integration solutions should enable all business users to leverage data for active decision-making. Companies that get this right will find themselves better …
Can Bridging Data Literacy Gaps Create Better Analytics Outcomes?
Every department, from marketing to HR to product to IT, requires the heavily use of data for day-to-day tasks. As such, employees will need far more data …
apply(conf) puts everything on the table to help data and ML teams succeed
Bringing ML models into production is hard. Fortunately, community initiatives such as apply(conf) are helping.
Real-time Analytics News for Week Ending May 14
In this week's real-time analytics news: Red Hat made numerous announcements related to automation, cloud, edge, and Linux at its annual Red Hat Summit event.
Data Fabric vs. Data Mesh: Key Differences and Similarities
Data fabric and data mesh both strive to bring organization to the data that is spread across the databases or data lakes. Data fabric is very …
Is the Data Cloud Alliance for Data Openness or for Google?
The Alliance believes that by committing to open data standards, access, and integration between data platforms and applications, it can significantly …
How Wide Data, Not Big Data, Provides More Prescriptive Recommendations
For companies to effectively use their data for AI for predictive purposes, a variety of data, and especially wide data, must be