CHAPTER 1: OVERVIEW OF BUSINESS ANALYTICS (Chapter Content) Overview of business analytics Origin of business analytics Business analytics Business intelligence Big data and business analytics Four aspect of big data OVERVIEW OF BUSINESS ANALYTICS - to explain the business analytics, you have to make a lot of assumptions that generalize the challenges organization have with making using business data to make good decisions. tools with which people can disseminate the data that’s been collected, to produce meaningful conclusions (Fulton, 2013) - Business Analytics is the study of data through statistical and operations analysis, the formation of predictive models, application of optimization techniques, and the communication of these result to customers, business partners, and college executives (Galleto, 2018) - making decisions is the most important task in the role (Business Analytics) - ginagamitan ng data / mathematical computer based model - art of assembling data gathered - portion of business intelligence according to Fulton - organization have been employing business analytics to analyze their data for decades. Every organization has different data and a different approach to analyzing it. There is no one size fits all business analytics solutions. - to gain more insight the company - Summary - has a direct impact on organization’s strategic, tactical and operational business decisions. BI supports factbased decision making using historical data rather than assumption and gut feeling. ORIGIN OF BUSINESS ANALYTICS - focus on financial BUSINESS INTELLIGENCE - From ancient times, people have had this need to predict the future. They have used crude methods like stones and sticks to project how much crops they were going to harvest or how they were going to yield. - process of collecting information from all sources to make data-driven decisions in an organization (Fulton, 2013, Galleto, 2018). - mga taong naka dipende sa mga bagay bagay - process of combining aspects of reporting, monitoring and alerting, dashboards, scorecards, and ad hoc query data exploration (Caspistrano, 2018, Galleto, 2018). - they use stick and they predict how many they are going to harvest - 1970 computer’s created. - giving the right decisions at the right time to the right person - contains messy information / inaayos ang mga data or information BUSINESS ANALYTICS - business analytics is one of the most talk-about topics in the field of business and information technology. An as expected, business analytics is becoming one of the most sought-after courses in the academe. - Business analytics is the art of assembling the data gathered through business intelligence in such a way that it can be analyzed by people. It is comprised of the BIG DATA AND BUSINESS ANALYTICS - Statistical Analysis System (SAS) defines data as a term that describes the large volume of structured and unstructured data which can be analyzed for insights needed for better decisions and strategic business moves. IBM, in the other hand, refers to it as data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low-latency. - involved machine automation to analyze data (FOUR ASPECTS OF BIG DATA) VOLUME o Volume is the base. The main characteristics that makes data “big” is the volume. It makes no sense to focus on minimum storage unit because the total amount of information is growing exponentially every year. Volume has to do with the ever-increasing size of the data and databases. o Refers size of data sets VARIETY o Describe the organization of the data including whether the data are structured or unstructured. It is considered as the complexity of the data in this class. A wide variety of data is available from such sources as mobile phones, videos, text, retail scanners, internet searches, government documents, multimedia, empirical research, and many others. o Many different forms of data VERACITY o Veracity refers to the trustworthiness of the data, because it has to do with data quality, correctness, and accuracy. This includes provenance and curation. Provenance is based upon the pedigree of the data, the metadata and the context of the data when collected. Curation is an integral concept that binds veracity and provenance to principles of governance and data quality assurance. o Trustworthiness of data / quality of data o Indicate to reliability, authenticity and legitimacy of data Provenance – protecting security Curation – improve wrong data like fixing errors VELOCITY o Velocity refers to the speed with which data is generated with which the data are available and with which the data can be processed. The velocity characteristic of data is important in ensuring that data are current and updated in real time. o Frequency of incoming data