Mashup Data from Anywhere: Mashup any data source including relational databases, web, flat file, or Big Data repositories into a logical semantic layer. Decoupled data models speed model preparation, data management, and user access. Hybrid Data Management: Seamlessly combine multi-source models and live data for analyst consumption from a single hub. The following features will give you these capabilities: To optimize your BI, look for a solution that can combine multi-source data into reusable models, connect live data with a high-performance data engine and enable multiple analysis from each flexible data model. Whether you’re managing complex enterprise data from many sources or scaling governance and adoption, your choice of enterprise BI platform should simplify and optimize IT workflows to reduce operational costs and resource expenditure. It is possible to simplify complex Enterprise BI ? With optimized IT workflows, business teams can lead more effective campaigns, optimize business operations, and solve business-critical challenges fast. Consider what customer service you’ll receive from your provider, and how you’ll be supported from onboarding to expansion. This leads to faster, better-informed reports and ad hoc analyses that help businesses reduce costs and make decisions based on data faster.Īnother important consideration is the ease of migration from other BI systems, and the ease of deployment. Your solution should enable you to create a layer of administration and governance between IT and the analysts, allowing IT to be the data steward instead of the hands-on data wrangler. Ensure that your solution has a wide range of database connectors, so that you can speed up analysis from less efficient data sources or query data live from high-performance sources via a single user interface. A hub of this kind facilitates IT workflows for building flexible data models from any source, enabling easier adoption for non-technical users and eliminating back and forth between IT and business teams. Your ideal platform should simplify end-to-end BI management, drastically reducing time-to-insights by allowing business teams to autonomously analyze and visualize data of any size, from any source, via a single data hub. Realizing when the platform was really built for Enterprise BI The limitations of these technologies are exacerbated by clunky and expensive workarounds that require IT to manage multiple tools in order to get the best of both worlds. It creates business user autonomy at scale, while modern data-discovery tools grind to a halt when consolidating big data sources from several platforms with complex data or when scaling with more data. A platform of this kind eliminates usability barriers and long back-and-forths between IT and business teams common to traditional BI stacks. If you find yourself in this situation, you most likely need to select and deploy an end-to-end Enterprise BI platform that bridges the gap between legacy BI and modern data-discovery tools providing a single full-stack solution for your entire BI workflow at scale. In this paper, we’ll guide you through the things you should consider in order to overcome this problem and help you choose the best BI solution for your enterprise. However, today’s enterprise information technology (IT) organizations are often stuck between dated legacy business intelligence tools and limited data discovery tools. 
The Modern Platform for Enterprise Business Intelligence This shows why it’s critical for enterprise organizations to maintain agile and scalable business intelligence (BI) infrastructures that make big, complex data actionable. In a 2020 survey from Constellation Research, the companies that have infused data-driven applications into their daily workflows also happen to be the leading 20% to 25% of organizations, the innovators and fast followers.
Have you Future-Proofed your Enterprise Business Intelligence? Enterprise Business Intelligence: Choosing the Right Platform
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