Streamlining Planning and Data Collection for Self-Service Business Intelligence

Decision-makers in finance and operations are driving adoption of self-service business intelligence (BI) tools such as Microsoft’s Power BI so that they can develop data-informed forecasts, plans, and strategies. Not content to merely consume data in historical reports and dashboards, these users need real-time updates and the power to interact with increasingly large volumes of complex data for accurate planning, forecasting, and analytics. Organizations also want to expand self-service BI to support collaborative decision-making more effectively across functions. Critical to self-service BI is enabling users to bypass long IT data collection and preparation cycles and gain the right data at the right time. However, too often users are left with the choice between waiting in IT backlogs or using inadequate tools and processes that require considerable manual work and risk data exposure through unauthorized access. Performing what-if scenarios with accurate, timely data is too difficult. Fragmentation of processes for data collection, enrichment, modeling, and analysis add delays and inconsistency. Writeback capabilities for users to align BI with back-end data sources, applications, and platforms are either missing or too rigid, slow, and manual, with version control an issue. Getting the right data and fixing problems usually involves chasing down IT experts. Join this TDWI webinar to learn how you can streamline self-service users’ data collection and enrichment to improve collaborative analytics, especially for master data management, business planning, forecasting, and strategy. Speakers will discuss both important technology trends for self-service BI and solutions specific to Power BI environments. Topics this webinar will discuss include:

• How to streamline data collection, enrichment, and writeback directly within Power BI

• Improving collaborative planning, forecasting, and strategy by enabling all users to view, measure, and align performance targets with real-time data

• Empowering users to unify analysis, visualization, modeling, collection, planning, and writeback within self-service BI tools such as Power BI

• Reducing manual work and increasing automation to accelerate speed to insight

• How to transform data collection and enrichment for critical use cases such as sales & operational planning, supply chain planning, and master data management