Information is power and in this era of information, data comes hard and fast. So much so that we now have a phrase for it — Big Data. But, ever since we’ve understood the power and scope of Big Data, the foremost challenge has been dealing with it. How do we gather it, collaborate with other functions, analyze and apply it?
This is where the Microsoft Dynamics AX Business Intelligence comes in. Ever since its launch in 2015 Power BI has been one of Microsoft Dynamics AX’s strongest tools. The catchphrase “seconds to signup, minutes to wow” has proved pretty effective. It performs one of the most essential tasks in the Microsoft dynamics 365 implementation services — making sense of the data.
Need for Power BI
That we need information when making business decisions is a given. But this is no longer limited to a simple talk point or a bullet list of ‘things you need to know’. Data itself has become complex today. Business leaders are now required to be data knowledgable with at least a working knowledge of concepts like machine learning, data manipulation, and statistical analysis and projections. They must be able to understand this as they access it and not rely on ‘experts’ to simplify all details.
Moreover, this data has to be available at all times and at every level. With business decisions now involving a number of complicated factors, we need access to a diverse set of data that must be analyzed in real-time in a format that can be easily understood. We need advanced analytical functions like data visualization, predictive analysis, and integration at a daily basis in a format that keeps evolving with the changing dynamics and capabilities of an organization.
Obviously, traditional means of data software would be completely inadequate. Power BI in Microsoft Dynamics 365 gives us a set of tools that facilitate the collaboration of data, advanced analytics, and access.
Once you have all the information, what do you do with it? What you need from data, is an indication of how your decisions will pan out. For instance, when launching a new product we often study responses to similar products, our own brand image and the feedback from a sample group. The data is then analyzed to forecast the success of our own venture. In other words, what we are looking for is predictive analysis.
Predictive analytics: Predictive analysis is the process of looking at available data to predict a future result. The challenge here lies in the sheer scope and size of business data. Not only must it work with a large amount of data, but it must also accommodate new sets of data as it flows in. Because businesses deal with a multitude of decisions and varied sets of data, any analytical tool must also be able to switch back and forth as per demand.
This requires machine learning. It may sound like science fiction, but machine learning is very much a part of our life today. The Azure Machine Learning Studio in the Power BI can evolve with data, helps you visualize the machine algorithm.
R integration: Just having information is no longer enough. It must be available in a format that can be understood quickly and efficiently. R Language is widely used by statisticians and data analysts and Power BI integrates the R language to generate insights. It allows for the visualization of data. The visuals can be added to reports or shared through the dashboard. But you don’t really need to know about R to work this. Custom visuals give you a ready format to work with. It si also part of the BI service and does not need a separate R installation.
Quick Insights: The Power BI has a Quick Insights feature that uses advanced analytical algorithms to acquire insights from the given set of data. Developed by Microsoft Research, Power BI works in a time-bound manner. You can even optimize the data to make it ready for analysis. To make matters simpler, Quick Insights has a visual display. Data is arranged in 32 separate cards. These insight cards arrange the data in an easily understood format like a graph or chart along with a short description.