Fragmented data is a leadership challenge: when key concepts mean different things across systems, trust erodes and decisions slow down. Metsähallitus built a shared conceptual model (1,400+ concepts) with DSharp to make metrics consistent and reusable across teams. Next, they see potential in DSharp Scout to guide users to reliable, traceable answers.
Monessa organisaatiossa dataa on paljon, mutta numeroihin ei luoteta, kun käsitteet elävät eri järjestelmissä eri tavoin. Metsähallitus ratkaisee haastetta DSharpin käsitemallinnukseen pohjautuvalla data-alustalla, joka tekee tiedosta yhtenäistä ja päätöksentekoa tukevaa. Yhteiset käsitteet ja mittarit nopeuttavat arjen työtä, vähentävät tulkintaa ja parantavat raportoinnin laatua.
Data Warehousing, Business Value and Practical AI event in Helsinki on the 3rd of December Data warehousing and AI are changing fast. TDWI brings together leading experts to Helsinki to explain how organizations can turn data into real business impact, and how AI can support analytics without creating risk. On Wednesday, December 3rd, from 9:00 […]
Peek Data Projects and DSharp Data Solutions are proud to announce a new partnership aimed at making data modeling, reporting, analytics and data warehousing more accessible, transparent, and efficient in the Benelux area. By combining Peek’s proven expertise in business-driven data projects with DSharp’s innovative reporting, analytics and data warehousing tools, the companies are creating a powerful foundation for smarter, more cost-efficient reporting solutions.
The era of hourly consulting is reaching its limits. For years, organizations have paid experts to rebuild the same pipelines, dashboards, and definitions again and again. That model was defensible when tools were immature and every solution had to be crafted by hand. But with automation and AI reshaping the landscape, the real question has shifted.
Varha, the wellbeing services county of Southwest Finland, set out to build a unified data foundation and develop its data leadership capabilities. Agile collaboration was essential in the project. Planning and executing the work in quarterly cycles proved effective for advancing this large-scale initiative. DSharp’s DSharp Studio was the chosen software for the automation of the data warehouse.
