Top Business Intelligence Trends for 2016 by Panorama Software

According to a recent Forrester survey, while 85% of organizations want to improve their use of data insights in their decision-making, 91% of the respondents report that they are not able to improve upon their data-driven decision-making.

Business users have a tremendous appetite for data. The “single version of the truth” was a rallying cry to deliver business data in data warehouses for years. Users were able to digest and analyze large volumes of corporate data. They reviewed trends, identified anomalies, and supported decision-making because they had the detailed data to support action. As the business/data environment matured, the need for more diverse detail and increased delivery speed only grew. The data lake became a successful mechanism for delivering data from diverse systems in a timely manner.

Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics. Where are organizations heading in 2019? How are analytic and data warehouse architectures evolving to enable faster and deeper self-service analytics and BI for organizations looking to create a competitive edge? How is public, private and hybrid clouds factoring into deployment decisions? What are the hottest open source projects from Apache Spark to Kudu, Kafka, Hadoop, and beyond?

Today, most web and mobile applications are limited to “lightweight” analytics because general-purpose databases can be optimized for transactional or analytical workloads, but not both – and since transactional processing is critical, applications have to compromise on analytics. However, what if an e-commerce application could let customers know which products are soon to be sold out based on clickstream data, shopping carts, current inventory and recent purchases as well as historical buying patterns and emerging shopping trends? In this webinar, attendees will learn how to leverage MariaDB ColumnStore to provide transactional applications with real-time analytics on historical data.