Microsoft Power BI, the new cloud-based data analytics and visualization tool, took center stage at the software vendor's Convergence 2015 show in Atlanta. But the conference also highlighted the fact that there are more fundamental CRM issues for users to solve, as explained by Lauren Horwitz, executive editor of SearchCRM and SearchContentManagement, in this episode of BizApps Today.
Power BI enables business users to gain access to data through dashboards with easy-to-read charts and graphs. Horwitz said that in his Convergence keynote, CEO Satya Nadella demonstrated how Microsoft itself is using Power BI to track feedback from Windows 10 beta users about planned new features and build it into the development process.
While the public release of Microsoft Power BI was a main event at Convergence, many Microsoft users said they were dealing with core CRM concerns, such as integrating front- and back-office data. "A lot of users are still struggling with basic bread-and-butter issues, like choosing a cloud-based CRM to enable front- and back-office integration," Horwitz said.
For example, City Harvest -- a nonprofit food "rescuer" that gathers food from grocery stores and other locations and distributes it to needy organizations throughout in New York -- has used Microsoft Dynamics CRM and ERP to pull together data to help ensure that it delivers the right food to the right organizations. Horwitz said that if an organization has vegetarian or kosher needs, City Harvest can identify appropriate donors, deliver the needed goods and, once the delivery is complete, update its ERP and CRM systems in real time on mobile devices.
Jack Vaughan, news and site editor of SearchDataManagement, also discussed in the video why the new Apache Spark framework has garnered interest as an adjunct -- or alternative -- to Hadoop for big data processing and analytics. Vaughan said Hadoop and Spark have similarities, but Spark may gain a leg up for various reasons. "You have to wonder whether people are ready for another distributed computing framework," he said, but added that Spark seems attractive for a few reasons:
- Spark has a higher-powered compute engine than MapReduce, the original application engine in Hadoop. That's partly because Spark works more in-memory, whereas MapReduce-based Hadoop applications have more heavy disk-based "hauling and lifting" to do.
- Spark is more general purpose and more attuned to analytics than batch-oriented MapReduce is. In addition to batch processing support, it has pre-built libraries for machine learning, data streaming, graph processing and SQL querying applications.
- Spark supports a variety of programming languages, so it's more likely that companies have developers in-house with the skills to work in Spark.
Despite this solid foundation, Spark is still emerging and not necessarily ready for prime time, according to Vaughan. The crowd at a recent Spark Summit conference in New York indicated that "Spark can exist east of Berkeley," he said. "There is potential, but there is a lot of learning to do."