The Institute of Analytics Professionals of Australia (IAPA) is the professional organisation for the analytics industry, incorporating business data analytics, business intelligence, data mining and related industries.
Analytics is the discovery, interpretation, and communication of meaningful patterns in data; and the process of applying those patterns towards effective decision making. In other words, analytics can be understood as the connective tissue between data and effective decision making, within an organization. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. BI technologies can handle large amounts of structured and sometimes unstructured data to help identify, develop and otherwise create new strategic business opportunities. They aim to allow for the easy interpretation of these big data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability.
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information from a data set and transform the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data; in contrast, data mining uses machine-learning and statistical models to uncover clandestine or hidden patterns in a large volume of data.
IAPA as an organisation
As an organisation, it provides information sources, a "virtual community", a "networking hub" and a "professional identity". IAPA promotes the benefits of analytics in modern business, emphasising the increasingly strategic role played by data analysis in the business arena.[citation needed]
Chapters have been established in Sydney, Melbourne, Canberra, Brisbane, Perth and Adelaide. As of October 2012 IAPA has over 2,400 members and runs quarterly meetings in each location providing industry speakers and an opportunity for members to network.
The IAPA website acts as the portal for Analytics professionals in Australia, providing information on relevant Events, Articles of interest and Special interest groups.
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