Business intelligence (BI) and mobile have been treated as separate areas of technology and potential strategic advantage for years. But continuing to do so could be a mistake. Mobile is redefining the way people use technology and companies must address those changes.
At the same time, BI grows in importance as retail industry increasingly recognize that they must embrace data-driven decision making. Although BI initially was restricted to desktop machines and servers, users won’t freeze in place and do things the way they always have. People expect to use smartphones and tablets regularly in their work.
By moving BI into mobile implementations, Retail industry can bring information critical to making decisions to the point at which many of those decisions are actually made. The most obvious benefit is that instead of being restricted to a relatively small group of experts and elite users, the technology can now be made available to large numbers of employees who are at the forefront of a company’s operations.
Real-time data can also be used to avert crises. If your Retail Company has, for example, posted something on social media that’s generating controversy, a retail analytics solutions in canada and mobile BI platform with sentiment analysis capabilities could alert you instantly of the shift in public sentiment, allowing you to take swift action and get control of the story before it snowballs into a PR disaster.
Mobile BI is not just a tool that access from anywhere, it’s about data visualization and manipulation from anywhere. It’s also about allowing your team the freedom to work from anywhere at any time. For example, if a new theory about business marketing strategy occurs to you in mid night, you can put your smart phone and get the relevant data from Mobile BI like board, then you can easily use that software to arrange the data in a variety of visualization formats like charts, graphs etc.
Alrasmyat provide Retail analytics solutions in canada with Mobile BI Platform to helps retail industry to manage their data in an efficient way. Companies can also use this data in decision making process.