Term Data Analytics

The term data analytics is dedicated to information that is analyzed from one or more sources and utilized to formulate decisions. In essence, it’s the art of analyzing information and is used in scenarios that require a holistic approach of making informed decisions. With that, collective past practices and concepts are incorporated to generate qualitative properties of decision-making. Business data analytics dates back to the mid 1950’s and was most utilized to gather a large amount of information in a short period of time. This would mark the beginning of using data to impact management decisions.

Business data analytics has transformed over the last several years and was considered an era of real time progression towards an objective, understanding of the concept and provided managers factual information that went beyond the ability of making informed decisions. With this, information pertaining to procedures and customer interactions were analyzed in depth. In the early stages of data analytics, the focus was based on computing technologies that were mainly built by large businesses and later taken on by marketable wholesalers; it was considered the era of business data warehouses and widely used to capture information for reporting purposes (Davenport, 2013, pg. 4). Although this form of collecting information was beneficial, businesses’ needed new capabilities in order to manage the information. Many found that arranging the information for the warehouse was tedious. They had the means of preparing the information, but little time on its analysis. During this era, the progression of data analysis was slow, but the industry knew that it was advantageous to remain competitive, improvement of operational efficiency and making better-informed decisions (Davenport, 2013, pg. 4).

The basic conditions of data analysis was utilized up until the middle of the mid 2,000’s, until major internet organizations started to analyze new types of information. Large amounts of information was more distinguishable from small information, mainly because it did not have a single source of generation from a businesses internal system. In fact, it came from outside sources, such as the internet and public data initiatives. During this time, businesses understood the need for more aggressive tools and it became apparent that profits would increase if they were able to produce them. Also, they assesses that new data concepts needed to be acquired, because large amounts of data could not be processed fast enough on a single server, which was a receptive basis for group data processing; this concept would become well known as Hadoop (Davenport, 2013, pg. 4).

Today’s era of data analytics has prompted large businesses to emulate the large data companies in California; it’s not just business that provide information or the online company producing products based on the analysis of information, it was every business on every level.