As technology advances, so do user expectations. Many customers approach us hoping to boost their application’s analytics capabilities, which are often struggling to keep up with user demand. We see the same analytics challenges time and time again: Disjointed user experience — A lack of customization and functionality prevents your users from viewing data in a way that satisfies their needs. Few dashboards are built to serve the needs of many.

For our regular readers at Yellowfin, the role of self-service analytics in today’s organization is more than clear. This type of analytics is aimed at helping more people across the company access, analyze and understand their business data, so they can make data-led decisions.

Ternary consolidates billing data from customers’ cloud service providers, ISVs, and other data sources using BigQuery and other Google Cloud services.

Step right up, ladies and gentlemen, and witness the grand spectacle of the digital age! In a world where data is king, where information reigns supreme, and cloud data warehouses are multiplying like rabbits, there's a technology initiative like no other— data warehouse modernization! This article is the second in the series "Seven Data Integration and Quality Scenarios for Qlik and Talend," and answers everything you wanted to know about data warehouse modernization but were afraid to ask.

Unlock insights faster from your MySQL data in BigQuery through Dataflow JDBC Templates.

The nursing profession is in crisis. According to McKinsey, over 30% of surveyed nurses said they may leave their current patient care jobs in the next year, and for inpatient nurses it’s higher at 45%. Meanwhile, the average professional tenure of nurses dropped from 3.6 years to 2.8 years between 2020 and 2023. These alarming trends have healthcare systems on red alert. Ninety-four percent of surveyed health system senior executives said the nursing shortage is critical.

Is the generative AI honeymoon over already? After months of buzz around its transformative possibilities, excitement is now starting to be tampered by a growing concern on trust and data privacy. Just in the last few weeks, there have been several lawsuits launched against AI companies, including a well publicized charge of copyright infringement.

Consumer privacy has increasingly become important for businesses and individuals alike. As data is becoming more and more widespread, people are more worried about where their data is going, how it’s being used, and how it’s facilitated. This has made data security paramount and front-of-mind for many organizations.

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).