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Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of pastbusiness performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based ondata andstatistical methods. In contrast,business intelligence traditionally focuses on using a consistent set metrics to both measure past performance and guide business planning. In other words,business intelligence focuses on description, while business analytics focusses on prediction and prescription.[1]
Businessanalytics makes extensive use of analytical modeling and numerical analysis, including explanatory andpredictive modeling,[2] and fact-based management to drivedecision making. It is therefore closely related tomanagement science. Analytics may be used as input for human decisions or may drive fullyautomated decisions. Business intelligence isquerying,reporting,online analytical processing (OLAP), and "alerts".
In other words, querying, reporting, and OLAP are alert tools that can answer questions such as what happened, how many, how often, where the problem is, and what actions are needed. Business analytics can answer questions like why is this happening, what if these trends continue, what will happen next (predict), and what is the best outcome that can happen (optimize).[3]
In healthcare, business analysis can be used to operate and manage clinical information systems. It can transform medical data from a bewildering array of analytical methods into useful information. Data analysis can also be used to generate contemporary reporting systems which include the patient's latest key indicators, historical trends and reference values.[4]
Analytics have been used in business since the management exercises were put into place byFrederick Winslow Taylor in the late 19th century.Henry Ford measured the time of each component in his newly established assembly line. But analytics began to command more attention in the late 1960s when computers were used indecision support systems. Since then, analytics have changed and formed with the development ofenterprise resource planning (ERP) systems,data warehouses, and a large number of other software tools and processes.[3]
In later years the business analytics have exploded with the introduction of computers. This change has brought analytics to a whole new level and has brought about endless possibilities. As far as analytics has come in history, and what the current field of analytics is today, many people would never think that analytics started in the early 1900s with Mr. Ford himself.
Business analytics depends on sufficient volumes of high-quality data. The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available.[3]
Previously, analytics was considered a type of after-the-fact method offorecastingconsumer behavior by examining the number of units sold in the last quarter or the last year. This type of data warehousing required a lot more storage space than it did speed. Now business analytics is becoming a tool that can influence the outcome of customer interactions.[8] When a specific customer type is considering a purchase, an analytics-enabled enterprise can modify the sales pitch to appeal to that consumer. This means the storage space for all that data must react extremely fast to provide the necessary data in real-time.
Thomas Davenport, professor of information technology and management atBabson College argues that businesses can optimize a distinct business capability via analytics and thus better compete. He identifies these characteristics of an organization that are apt to compete on analytics:[3]