More than just a distributed caching solution, data grids also offer additional functionality such as map/reduce, querying, processing for streaming data, and transaction capabilities.ĭata Mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. The essential features of a BI dashboard product include a customizable interface and the ability to pull real-time data from multiple sources.ĭata Grids are in-memory distributed databases designed for scalability and fast access to large volumes of data. They may be tailored for a specific role and display metrics targeted for a single point of view or department. Dashboards consolidate and arrange numbers, metrics and sometimes performance scorecards on a single screen. In simple words, the aim is to segregate groups with similar traits and assign them into clusters.Ī business intelligence Dashboard is a data visualization tool that displays the current status of metrics and key performance indicators (KPIs) for an enterprise. Business intelligence is meant to take in all the data being generated by a business and present easy to digest performance measures and trends that will inform management decisions.Ĭlustering is the task of dividing the population or data points into a number of groups such that data points in the same groups are more similar to other data points in the same group than those in other groups. Business intelligence is a broad term that encompasses data mining, process analysis, performance benchmarking, descriptive analytics, and so on. Strictly speaking, business analytics focuses on statistical analysis of the information provided by business intelligence.īusiness intelligence (BI) refers to the procedural and technical infrastructure that collects, stores and analyzes the data produced by a company’s activities. Due to this close relationship, the terms business intelligence and business analytics are sometimes used interchangeably. Big data can be analyzed for insights that lead to better decisions and strategic business moves.īusiness Analytics is one aspect of business intelligence, which is the sum of all your research tools and information infrastructure. It’s what organizations do with the data that matters. However, it’s not the amount of data that’s important. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.īig Data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.Īrtificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition.

For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain and so on). For some, it is the process of analyzing information from a particular domain, such as website analytics. This huge data mass is what everyone is talking about and that with proper handling can bring significant results and changes for all those industries and for human life.Īnalytics has emerged as a catch-all term for a variety of different business intelligence (BI) - and application-related initiatives. Nonetheless, researches has found that less than 0.5 percent of that data is actually being analyzed for operational and business decision making.īy the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.īy then, our accumulated digital universe of data will grow from 4.4 zettabytes today to around 44 zettabytes, or 44 trillion gigabytes.Īccording to IDC, the number of connected devices within IoT universe will be 30 billion by 2020 and forecast is a potential market estimated in 7.3 billion dollars yet in 2017. Moreover, solely along 2017, a wide and growing range of data coming from all type of industries: financial, IoT, healthcare, automotive, astronomy, biotech, cybersecurity, social media, entertainment, amongst several others, can make even higher these impressive numbers. More data has been created in the past two years than in the entire previous history of the humankind.

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