Outer joins (preview) - Release notes
An outer join (left, right, full) combines data from two tables, including all matching rows and any unmatched rows from one or both tables, filling in NULL for missing data. Analytical platforms use outer joins to achieve: Broader analytical capabilities: Ensure all relevant data is visible, even if there is no exact match in another table (e.g., view all products, including products with no sales). Identify Gaps: Easily spot data integrity issues and missing information or relationships, which is crucial for analysis and reporting.
Sisense Performance: A Billion Records in a Single Server
Browsing our site, speaking to our team, or reading about us in analyst reviews, you might have noticed that we dig technology here at Sisense. That’s why when clients and prospects desire to push the limits, both in terms of data complexity and quantity, we happily oblige.Does Your Project Have A Timeline? Planning For And Defining Success
Timelines are a key component of any dashboard implementation. Considering the available time is vital to establishing reasonable goals and how to best prioritize tasks. More importantly, adoption improves when projects show fast results instead of dragging on endlessly. Planning a roadmap for implementation can produce a successful integration for you and your team.
Driving sales and cutting losses: How MPP uses Sisense for smarter decisions
How does a warranty company like MPP balance boosting dealership sales while keeping costs in check? With Sisense, we’ve unlocked the power of data to make smarter decisions. From analyzing contract production to uncovering inefficiencies in our claims process, Sisense helps us support dealerships in driving sales, cutting unnecessary costs, and building lasting customer loyalty. Read on to see how Sisense fuels actionable insights and strengthens partnerships at MPP!
