3 New Trends of Business Intelligence

Business Intelligence is a powerful and useful concept that, like the data it analyzes, is always changing.

New technologies, cloud data, even hours spent with the data can help or hinder your next move. If you use effective business intelligence training in your organization, you can improve the decision making processes at all levels of management and improve the strategic management process. There are 3 top trends coming to Business Intelligence to keep a look out for: Cloud Analytics, New Technologies, and Data Visualization as Norm.

1. Cloud Analytics

In 2015, people began embracing the cloud. They realized putting data in the cloud is easy and highly scalable. They also saw that cloud analytics allows them to be agile. In 2016, more people will transition to the cloud thanks, in part, to tools that help them consume web data. Early adopters are already learning from this data, and others are realizing they should. And more companies will use cloud analytics to analyze more data faster. They’ll come to rely on it just like any other critical enterprise system.

2. New Technologies

There are a number of new technologies in the BI ecosystem. As these go to market, we’ll see gaps that need to be filled. There will be new companies to do just that. Hadoop accelerators, NoSQL data integration, IoT data integration, improved social media—each of these provide an opportunity for a new company to start up. In 2016, we’ll see the rise of the gap fillers, leading to a market consolidation. And organiza - tions will continue to shift away from single solutions and embrace an open and flexible stack that includes these new technologies.

3. Data Visualization as Norm

Data visualization software empowers data analysts and business users to develop charts, graphics and presentations that convey insightful information about business performance and opportunities. An emerging practice called data storytelling has evolved around the use of visualization tools to translate the results of analytics applications so they can be more easily understood by corporate executives and other decision makers in organizations.

But you have to be careful when attempting to craft a story based on data visualizations, especially when you've been steeped in the analysis work for so long that you become blinded by the familiarity of the content. To ensure that you're delivering the intended message to the appropriate audience, you might want to begin by asking some questions about the objectives of a data story and the process for disseminating it within your organization. Also, to avoid 'over-decorating' data visualizations, effective organization and graphical consistency are both called for.

Jun 2016

By: Jesse Amos