what is business intelligence?
Business Analytics relates to the exploration of historical data from many source systems through statistical analysis, quantitative analysis, data mining, predictive modelling and other technologies and techniques to identify trends and understand the information that can drive business change and support sustained successful business practices. Business Intelligence is looking in the rearview mirror and using historical data from one minute ago to many years ago. BI is important to improve your decision-making based on past results.
And also,in business intelligence one term can mean different things to different people, depending on their business focus and their perspective.
Business Intelligence is needed to run the business and is focused on creating operational efficiency through access to real time data enabling individuals to most effectively perform their job functions. It also includes analysis of historical data from multiple sources enabling informed decision making as well as problem identification and resolution. Traditional business intelligence (BI) has been focused mostly on reporting. In this approach to BI, highly-formatted reports are created by a few people typically report developers and distributed to an entire department or organization.
Analytics is a function of BI
BI used to refer to platform capabilities to access data, manage metadata, development tools for reports, dashboards, and applications, and publishing, scheduling and distribution capabilities. Analytics referred to either methods of analyzing information (i.e., descriptive, predictive, regression, neural networks, etc.) or the tools to perform those methods.
Thus, analytics is a subset of the broader platform capabilities. Industry leading BI platforms now include increasingly more complex tools to perform different types of analytics descriptive analytics, visual patterns discovery, and predictive modeling and data mining. The value of a BI platform providing such tools is that the results of analysis performed by highly trained analysts can be packaged in reports and dashboards. Some platforms can even provide this information in the form of apps that are intuitive and easily shared with millions of operational users to perform their own analysis with a few clicks. Business Intelligence (BI) is essentially a noun, in that it is an umbrella term of the overall scope of acquiring, persisting, warehousing, analyzing and reporting insights along with everything else in its periphery. Business Analytics on the other hand is more of a verb, the act of discovering insights using any tooling or services at your disposal.
Years back you would need to buy Business Intelligence platforms from mega vendors like Oracle, IBM, SAP or Microsoft. The cost of the software and the complexity of putting everything together puts BI firmly out of reach for most SMBs. Cloud services have since helped as many business no longer need to build their own BI infrastructure as the SaaS providers are performing all the gathering, persisting and reporting themselves. However this is where the 80/20 rule kicks in, as every business will inevitably want to look at data in a different way and supplement with other bits of data. This is where Business Analytics kicks in, the SMBs no longer require a full scale Business Intelligence infrastructure; they simply require the tools to gather data from these different sources and perform Business Analytics.
New generation tools like Clear Analytics no longer insist on a Business Intelligence infrastructure to be present to deliver, well, Business Intelligence. These tools should be able to fetch and present data regardless of where it resides, buried inside spreadsheets, in a database or in SalesForce. The key challenge now is to present this data to users in a manner which does not require any significant training or specialists to hire. At present the most dominant tooling for Business Analytics is Microsoft Excel, everyone who has graduated has some level of experience and thus the preferred platform. Clear Analytics leverages the ubiquity of Excel to deliver the data with the added benefit of automation, security, auditability and accountability; aspects which Excel inherently lacks. The result of which is that SMBs can now get the full Business Intelligence experience without the whopping pricetag.”
Analytics as a way to consume intelligence
There are a lot of conflicting views and opinions on where the lines are drawn between business intelligence and business analytics. A lot of it seems to be based on marketing trends and what somebody is trying to sell.
A tested definition of this exists in the CIA, the Central Intelligence Agency. The CIA is responsible for having the people and processes and infrastructure in place to capture data (contextual and numerical) from around the world, but also need to analyze, disseminate and strategize around how to intelligently apply the intelligence and output of the various analysis actions done to it. The intelligence teams exist to capture, analyze and strategize around the information (intel.) All types of analysis are different ways of using the intelligence collected in an intelligent way to make smarter decisions. In that way I would define Business Analytics as the collective set of methods and tools used by analysts to intelligently consume intelligence towards enabling smarter decisions about the business moving forward.
Analysis without intelligence can't be done that's guessing and intuition (which still rely heavily on informal intelligence.) Analysis that isn't Intelligent is dumb. Capturing intelligence without doing analysis is a waste of time, and Intelligence that isn't based on analysis of intelligence isn't Intelligent.