Business Intelligence vs. Big Data

BI, Business Analytics, Big Data are progressive steps up the information maturity scale.

Business Intelligence and Business Analytics are quite equivalent to many business stakeholders. The objective of both is to control business data through different techniques, processes, and technologies to deliver insights and enhance decision making. Analytics and Intelligence always boil down to only one thing – Data. Business Analytics and Business Intelligence is all about collecting and making sense about raw data and understand what happened & how it happened and predict future activity and planning. However, from a process and deliverable perspective, they have a different focal point:

BI is a process of the historical data and presenting the business hindsight & insights to the business - how the business processes are tracking, how the KPIs are measuring up, etc. It encompasses various forms of reporting (reports, dashboards, data visualization, data exploration tools) to present the insights to the business. BI gives the "now" and historic views of the business, integrated across the business lines.

Business analytics is more a process of real-time data to derive additional insights or foresight from the organization’s information. It can be predictive (sales forecast models, churn prediction models, etc.), or it can be to detect insights not previously known (correlations between aspects, segmentation analysis, customer profitability, basket analysis, etc.). Big Data is an attempt to assemble, cleanse, and structure all available data (with 3-V characteristics: Velocity, Variety, Volume) from multiple sources that impact business performance

The deliverable for BI is a reporting tool that allows business managers to view graphs and tables reporting the performance of the business, cross-functional processes, and his/her own functional area(s). Ideally, these metrics align and support the business strategy. The BI report should enable the manager/user to analyze the data with the interactive slice, dice, and roll-up, drill-down, -across, and -through pivot functionality.

The deliverables for BA are statistical models often used to predict behavior based upon analysis of large amounts of data. Business analytics are the tools that help you uncover nonintuitive insights from the information. They use sophisticated algorithms to identify and analyze patterns in a company's data in order to find relationships that may predict customer behaviors and purchasing patterns. 

 Business Intelligence as a data process, offering slice-and-dice, drill-down, and trend analysis capabilities. BI also provides key performance indicators and visual tools, such as gages on dashboards.

 Business Analysis may result in the development of BI solutions, but is a problem-solving (technology solution-building) process, usually framed around a Life Cycle Methodology (LCM). As LCM are practiced, BI and/or various other tech solutions may be deployed. Of course the advanced analytics models (with their own life cycles) is a very important aspect to highlight. The nature of the model (what it does, what it needs, what it provides), the role of the model, and its life cycle ("training" on representative data and "for real" running on production data, model regeneration after decay, etc.) are often the most complex part we have to explain to potential clients.

Both domains (Business Intelligence and Analytics) can definitely leverage, in their own ways, historical data (batch, data mining), and real-time/stream or near real-time analysis as well as predictive modeling. It is logical to say BI, and Business Analytics, Big Data is progressive steps up the information maturity scale and they are very closely related.