How to use BI for Data Analytics

 In Analytics, Business Intelligence

Business Intelligence and Data Analytics are mutually interdependent and coexist in the cohesion of each other. For a clear understanding of how to use BI for DA, firstly, we need to understand what BI is, and also what is data analytics and how data analytics is dependent on BI.

Business Intelligence

It is essentially a data-driven decision-making support system. BI is an incorporation of systemic ways and means through which data is collected, collated, analyzed, shared, visualized and reported, all to the aid of better-informed decision-making.

Data Analytics

Data analytics is the supplementing predecessor of BI. Once, we have all relevant data at our disposal and facts presented; this is the time to ask specific questions and glean predictable certainties from it. It is essentially compartmentalizing complex structures into easily agreeable forms for the sake of better understanding of the whole.

 

How to use BI for Data Analytics

In simpler terms,  in a sequential follow up, organizations ought to do these things necessarily: Once an organization, through Business Intelligence comes to know what is happening to their business, they intuitively explore to know – “Why it is happening?” and furthermore would also like to know “What will likely happen in future?” And here starts the realm of Data Analytics.

While from inception BI stands for – What is happening to your business (for visibility), the preceding questions, i.e., Why it is happening & What will likely occur in future set the stage rolling for the commencement of Business analytics which holistically deals with the investigation, prediction, and prescription. This very process of ‘business analytics’ per se encompasses Data Analytics in its entirety. And the Data Analytics facilitates the process of Business Analytics; this is where the role of Data analytics lies.

Role of Data Analytics in Business Intelligence

Diagnostic Analytics(Why) – In business analytics, to initiate the needful corrective measures, diagnostic analytics comes handy. Through this very process, you differentiate the whole complex structure and come to grasp why a certain thing is happening at a certain place. Now, as you have the requisite information with evidence, you can chart your future course in the best suitable way to avoid failure or enhance performance.

Predictive Analytics (What will) – As from the aforesaid process an organization is well aware of the wherewithal of its products or projects or the organization itself, now, the organization must want to know; by this rate of productivity where we will be heading in the future and if the organization intends to improvise then what would be the required essentials that must be followed or achieved in due course.

Prescriptive Analytics(Next best action) – Now, that the whole state of affairs is known, the intended ‘end views’ are targeted with Prescriptive Analytics. This process of analytics deals with – what is the best suitable set of tactics or strategies that ought to be followed so that in all likelihoods, after a period, we will be in our intended or desired position. Prescriptive analytics is a set of tools through which correctional measures that need to be followed or observed in letter and spirit to define the improvisation that is objectified as goals to be achieved.

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