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Business Intelligence (BI) software and analytics software are some of the most primarily and widely used solutions for data management. However, each set of tools has its own functionality and differs from the other in terms of parent technology.
Business analysts, data scientists, and software buyers often remain unclear about the key differences which separate analytics from BI practices. BI offerings aim at aggregating and analyzing current, actionable data to improve business operations, and are touted the most valuable tools available for managing data. Business analytics solutions, on the other hand, analyzes historical data to predict business trends and forecast future. Analytics proves resourceful in preparing for change, or for general improvement.
Business Intelligence helps streamline current operations
BI tools are simply softwares that helps enterprises to create dashboards from the key data being originating out of various process and department within the organization. These processes could comprise of sales numbers, productivity measures, or financial transactions, noticed daily. Some of the most prominent solutions include QlikView, SAP BusinessObjects, IBM Cognos, and Microstrategy.
Enterprises make extensive use of BI systems to maintain, optimize, and streamline current operations. Powerful reporting and data analysis capabilities are some of the key operational benefits enterprise realize as a result of leveraging the scope of BI. Moreover, BI systems allow managers to generate intuitive, readable reports that contain relevant and actionable data. In other words, BI solutions are designed, so as to improve operational efficiency and organizational productivity.
Comprehending analytics from an enterprise perspective
Similar to Business Intelligence, analytics-based systems also collate and analyze data in the process of identifying and addressing an organization’s weak points. However, there are few differences which separate analytics from Business Intelligence.
Analytics-based systems assist in identifying business trends in the past by leveraging various techniques. Statistical analysis, data mining, and quantitative analysis are some of the notable analytics-dedicated techniques used by various organizations. The data obtained from analyzing the business trends is used in predicting and preparing for adverse business scenarios in the future. Strictly speaking, business analytics makes use of predictive analysis to address problems before they occur. Some of the most widely used statistical tools are SAS, R and SPSS.
Keep in mind, that there are lot of overlaps between BI and Analytics and at times it would be difficult to distinguish between these two. After All, both are about analyzing enterprise data and helping organization take key decision out of it. A straightforward way to distinguish BI and analytics is the level of complexity present. BI is about reporting or presenting enterprise data into easily understandable format for management to make key decisions. Analytics is more than just presenting data, it is about finding needle in the haystack of large, unorganized data that organizations generate today.
How to select between BI and analytics offerings to address the needs for an enterprise?
Both the techniques prove resourceful in streamlining operations for an enterprise, or aiding towards enhancing productivity. However, the subtle differences reflected by the two techniques sets foundation for the technologies to be leveraged for addressing diverse business needs. As indicated earlier, BI systems make use of past and current data to optimize the present business scenario for success, while analytics works on the past data and analyzes the present, so as to prepare businesses for the future impediments or decide on how to increase top line or optimize expenses.
As discussed earlier, BI helps in identify the weak points in a business, and devises actionable solutions to tackle the issues. The technique proves promising for businesses needing intuitive reports and extensive data (or, data warehousing needs). Moreover, BI enables managers to improve decision making, besides assisting them in understanding their organization’s productivity, work processes, and employees. This comprehension of organizational practices enables them to improve the business from the ground up.
BI might not always prove that useful, as enterprises must additionally leverage analytics-based solutions to stay ahead of the market competition. For a new organization, or for an enterprise going through significant changes, the use of analytics can weave magic. Analytics-based systems do everything to ensure that a business makes the right changes, by utilizing historical data, current information, and projected trends.
In other words, analytics is the most appropriate solution for analyzing a company, the relevant market, and the related industry; while optimizing current performance, and predicting future business trends. However, most businesses today aim towards fostering a combination of current success and future preparation.
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