Data Engineering

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

whitePaper | November 18, 2022

It’s time to treat data like a product, not an afterthought. A new paradigm has emerged among forward-thinking data teams: treat your data like a product. This may sound easy in theory, but it’s far from it! Product development processes have become incredibly sophisticated, with resources dedicated to reliability, adoption, feature roadmaps, and more.

whitePaper | August 9, 2022

This report shows you how a data catalog can help you easily find and then use the data you need.

whitePaper | December 22, 2022

The key objective of setting up data mesh or data fabric architecture is to enable the availability of quality data in a timely fashion to the right people in the right format. A data fabric is an architecture framework and a set of data services that provide frictionless data capabilities across a choice of endpoint applications or services spanning hybrid or multi-cloud and on-premises, by using rich metadata foundation and artificial intelligence/machine learning (AI/ML) automation.

whitePaper | April 19, 2023

Unplanned downtime is one of the most significant pain points for industrial manufacturers today, costing them an estimated $50 billion each year. The risk is even greater for process manufacturing, where a critical equipment failure could result in the loss of an entire batch, environmental hazards, or safety risks. The adoption of digital technologies, such as the industrial internet of things (IIoT), promises to mitigate these threats by forecasting equipment failures and catching faults before they lead to unscheduled shutdowns. However, in practice, several challenges arise when maintenance personnel and operations leaders work to implement an IIoT solution aimed at eliminating unplanned downtime.

whitePaper | September 26, 2022

Communications service provider (SP) traffic volumes are progressively increasing as networks evolve, user devices gain greater capacity, and applications engaging with advanced network data such as that from the 5G standalone (5G SA) network exposure function (NEF) start to deliver on customer expectations. Cloudification of network functions — virtualized network functions (VNFs) and cloud-native network functions (CNFs) — is placing new burdens on old systems and processes not designed to manage intent-based network architecture. Silos of data locked within many installed systems keep transformation efforts from reaching anticipated objectives.