what is the difference between business intelligence and data?
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Business Intelligence refers to the information required to enhance business decision-making activities. Data Analytics refers to modifying the raw data into a meaningful format. The prime purpose of business intelligence is to provide support in decision making and help the organizations to grow their business.
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Data are simply facts or figures — bits of information, but not information itself. When data are processed, interpreted, organized, structured or presented so as to make them meaningful or useful, they are called information. Information provides context for data.
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I usually think of it this way: While both information and data are types of knowledge, to me, information is knowledge in its very basic form, while data is a "special" type of information. In other words, data is usually gathered by observation, experimentation, record-keeping, or the like.
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An ODS is meant for operational reporting and supports current or near real-time reporting requirements whereas a data warehouse is meant for historical and trend analysis reporting usually on a large volume of data. An ODS contains only a short window of data, while a data warehouse contains the entire history of data.
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Big data involves larger quantities of information while small data is, not surprisingly, smaller. Here's another way to think about it: big data is often used to describe massive chunks of unstructured information. Small data, on the other hand, involves more precise, bite-sized metrics.
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A data warehouse is built to support management functions whereas data mining is used to extract useful information and patterns from data. Data warehousing is the process of compiling information into a data warehouse.
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What is the difference between OLAP and data warehouse? A data warehouse serves as a repository to store historical data that can be used for analysis. OLAP is Online Analytical processing that can be used to analyze and evaluate data in a warehouse. The warehouse has data coming from varied sources.
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The main difference between a data warehouse vs. ... relational database system is that a relational database is used to store and organize structured data from a single source, such as a transactional system, while data warehouses are built to hold structured data from multiple sources.
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Simply put, Data science is the study of Data using statistics which provides key insights but not business changing decisions whereas Business Analytics is the analysis of data to make key business decisions for the company.
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The difference between data integration and ETL is that the data integration is the process of combining data in different sources to provide a unified view to the users while ETL is the process of extracting, transforming and loading data in a data warehouse environment.
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One line difference between Data Warehouse and Business Intelligence: Data Warehousing helps you store the data while business intelligence helps you to control the data for decision making, forecasting etc. Data warehousing using ETL jobs, will store data in a meaningful form.
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An operational database query allows to read and modify operations, while an OLAP query needs only read only access of stored data. An operational database maintains current data. On the other hand, a data warehouse maintains historical data.
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Business Intelligence is a technology that is used to gather, store, access and analyzes data to help business users in making better decisions, on the other hand, Artificial Intelligence is a way to make a computer, a computer-controlled robot, or a software that think intelligently like humans.
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What is the difference between data and information as discussed in class? Select one: a. Data are things that are true, information is things that are believed to be true.
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Improved insights for big data Not only is business intelligence which utilizes AI providing more insights, but it's providing them in virtually, real-time. As AI integrated software functions with an “adapt and learn” model, it's able to continually improve its decision making and even cut down on execution times.
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ETL means extraction transformstion and load. It is a process of extracting the data, transforming it (converting it into any other format if required) and then loading it into datasource like mysql, cassandra etc. On the other hand, business intelligence is the process of transforming data into visualizations.
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The major point of difference between Data Science vs. Business Intelligence is that while BI is designed to handle static and highly structured data, Data Science can handle high-speed, high-volume, and complex, multi-structured data from a wide variety of data sources.