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Bissantz makes the Snowflake data warehouse usable for analysts, data scientists and specialist users – without any programming effort.

  • flexible scalability with increasing data volumes and users

  • variable costs for hardware and software depending on your requirements

  • available worldwide, with protection via geo-redundant data storage

  • cloud-based analysis and reporting tool – mobile and on the desktop

  • reduced IT workload by taking over standard tasks such as installation, updates and backups

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Analyze relational data multidimensionally.

Intuitive methods for ad-hoc analysis of Snowflake data in DeltaMaster.

Snowflake is a scalable and perfor­mant data storage and analytics plat­form. It was designed to connect organi­zations world­wide, across any type and size of data and a variety of work­loads, to enable seam­less data colla­boration. As a cloud-based data ware­house, Snowflake belongs to the relational data­base systems that Bissantz solutions can access directly.

By preparing Snowflake data in our business intelli­gence solutions, both power users and specialist depart­ments in the company gain easy access to infor­mation in the cloud. This enables clear, compre­hensible reporting and data analysis with no need for programming know­ledge: Relational data from Snowflake can be used multi-dimensionally in DeltaMaster – with common functions such as slice-and-dice, drill-down and roll-up, filtering, zooming, browsing and navigating.

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With the semantic zoom in DeltaMaster, spark­lines in pivot tables can be enlarged. The spark­line columns or lines are not simply drawn larger; rather, DeltaMaster uses the free screen space, which also increases as you zoom, to display additional infor­mation. Zooming there­fore leads to an increase in infor­mation content – hence the “semantic” zoom. This allows a smooth tran­sition from a cell graphic to a detailed labeled graphic.


Browsing with DeltaMaster allows you to examine complex structures quickly and reliably. In a star-shaped display, the hierar­chies from the data­base are fanned out, e.g. the organi­zational structure or the customer, article or material master. Using drag-and-drop, the hyperbrowser adjusts its color according to a trans­ferred key figure. This makes the drivers of this key figure immediately recognizable – and even hidden compensation effects.


Navigation in DeltaMaster explains a value within a table by showing how it is distri­buted across the elements of another dimen­sion. During auto­matic navi­gation, DeltaMaster decides which dimen­sion promises the greatest know­ledge gain and displays it next. This involves the use of a data mining process that considers, among other things, the spread of the value being analyzed. Alterna­tively, the navi­gation steps can be specified in advance or defined by the user directly in the report.

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