EMA Blog: Business Intelligence and IT Management

As the race to deliver the UAW heats up, EMA sees the following vendors working toward a convergence of the data warehouse and data lake: Ahana, Amazon, Cloudera, Databricks, Dremio, Google, HPE Ezmeral, Incorta, isima.io, Oracle, SAP, Starburst, Teradata, and Vertica. EMA also anticipates that vendors that successfully deliver a unified analytics warehouse will quickly eclipse data warehouse and data lake vendors, making them obsolete, except for targeted use cases and analytical projects.

To assess the likely winners in the race for the unified analytics warehouse, it is important to understand the various requirements of modern analytics programs and the unified analytics warehouse.

At SAPPHIRE Now 2019, SAP introduced new cloud services that reach far beyond their installed base and make them a solid option for anyone looking for application or analytics solutions in the cloud. The new data and analytics offerings are not a departure from their commitment to current customers; they extend increased business value for all medium and enterprise companies looking for rapid return on their cloud investments. 

Everyone wants to talk about how analytics is the future of network engineering and operations. The phrase “network analytics” is used by vendors of various stripes to imply that a particular technology is smarter and better than the average solution.

Ahhh, the annual resolutions list! A time-honored tradition when we all look at the new year as an opportunity for a fresh start.

In research done earlier this year, we looked at changing patterns of IT service management (ITSM) adoption across a population of 270 respondents in North America and Europe. One of the standout themes that emerged from our findings was the need for the service desk to become a more automated and analytically empowered center of [...]

Many times when discussing the topic of big-data, the focus is on the volume of the data, the structure of the data or the near real-time analysis requirements of the data.  We toss around buzzwords like Hadoop, structured vs unstructured, etc…. However, often times what is missed are the analysis goals of the big-data environment.

See Dennis’ recent blog post on the state of BSM Analytics, posted at BSM Digest, here: http://www.bsmdigest.com/bsm-analytics-what-are-they-and-why-should-you-care-part-one