QUIPU collects metadata from any source system in various ways. Databases can be accessed via JDBC connections, our ODATA connector gives you the power to extract metadata from open data API's. Our Excel import functionality even lets you describe your own data model to be imported.

Not all entities and attributes collected need to be propagated to your data warehouse. Our transformation module allows you to filter on metadata using powerfull regular expressions together with AND/OR logical operators. This module also allows you to add, convert or rename objects as well.

Graphically design one or more data flows in our advanced canvas. This is where modules and data models are dragged on screen and can be linked together to create the data flow needed. Choose for one diagram per source system, or create a diagram that shows all modules and data models per layer of your data warehouse. It is in your hands.

Using metadata and by applying patterns, QUIPU generates various data models needed in the data warehouse. From staging models to HDA models (Historic Data Archive), QUIPU not only generates the model structure but also the code to load the data.

Insight in the providence of data is an essential requirement. Our data lineage visualisation shows the origin of entities and attributes through the complete chain of linked models in your data warehouse solution.

Having stored all relevant company-wide data is not all. Our data model set generator assists you in creating the required subsets of data needed for specific usergroups. A guided selection of relevant entities and attributes helps you in delivering data solutions to where they are needed fast. Of course with the option to rename objects to make more sense to business users.

Updates to source systems occur in every organisation. When not communicated upfront to your data warehouse team this might result in errors during the load process. The model delta detector module compares data model versions, and can be used to detect changes in source models compared to what is expected. Presented in a fully customisable HTML page (using templates) it is easy to spot differences, i.e. new or removed attributes, changed data types or precision or in constraints.

One of the key distinctive features of QUIPU is the use of templates. Packed with a fully functional set of templates the user has all the flexibility to adjust these templates or even create new ones for any platform.Templates can be used to generate SQL code, but also HTML or any other type of code. By using global properties, standard or dynamic code can be injected in our templates, providing even more flexibility. Templates are very powerfull in delivering reliable and executable code as output, every time.

Having insight in data provenance, or also called lineage of data, is a must-have for modern companies. Lineage is key when it comes to providing trust, authenticity and credibility of data, especially when data is being processed in a flow.  QUIPU makes data lineage visible on table level as well as on the level of attributes. Pick any table from a model to start with, and expand the lineage both up- and downstream.