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<\/a><\/figure><\/div>\n\n\n\nBusiness intelligence (BI) tools have always offered a very stratified approach to the data that’s supposed to inform decisions across entire organisations. Storing large amounts of data meant having a database that was complicated to manage and access, and running analytics meant working with\u00a0OLAP<\/a>\u00a0cubes and lengthy\u00a0ETL<\/a>\u00a0processes. Both the complexity of the technology and the cost of licensing meant that direct access to the data was limited and usually delayed — when it takes a day to run a report, you can’t have a real-time view of how your business is doing.<\/p>\n\n\n\n The power of Microsoft’s\u00a0Power BI<\/a>\u00a0<\/strong>isn’t just that it offers more visualisations of the data once you get it, alongside the familiar paginated reports from\u00a0SQL Server Analysis Services<\/a>\u00a0made self-service through Azure. It was always about bringing that data to business analysts and decision makers at scale, and giving them what we now call no-code tools to clean up the data and work with it without needing to be a professional data engineer,\u00a0Arun Ulag<\/a>, CVP of Microsoft Power BI, told TechRepublic.\u00a0<\/p>\n\n\n\n “To bring in data at scale and process it with Power BI Data Flows directly on Azure DB, with no code experiences, to be able to analyse unstructured text and images; things like sentiment analysis, key phrase extraction, language detection and image recognition are drag-and-drop no-code experiences built into Power BI.<\/strong>”\u00a0 Read On:<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"