Pattern based
model-to-model conversion
Patterns are everywhere!
If you look at nature you can recognize patterns in everything that grows. Patterns helped shape the world we live in. In physics, biology and in mathematics. With this in mind we reinvented QUIPU.
As BI-experts we focused on automation of the data warehouse. But looking at this from a distance we can only conclude that a data warehouse is nothing but a set of patterns. As are data migration, big data applications, specific data transformations and so on and so forth.
Over the years we met many customers with their specific data management needs. And still every time experts tend to sit down and use the tools at hand to start building the same solution they built over and over again. Hence introducing a lot of risk to companies because of custom and divergent coding and repeating the same boring tasks they did before to achieve the same results. This is exactly where a good expert distinguishes himself from a mediocre one. By searching for means that automate these boring tasks. Leaving the complex and hence the fun stuff to the expert to solve.
That is precisely why we reinvented QUIPU. To provide a platform based on a metadata repository that can automate whatever data management challenge. Thus reducing risk by generating high quality code based on meta data that does not need testing anymore. By creating and adding custom modules together with our customers we grow the capabilities of the platform. Using templates, that customers can maintain themselves to allow for implementation of the solution in their particular application landscape.
If you look at nature you can recognize patterns in everything that grows. Patterns helped shape the world we live in. In physics, biology and in mathematics. With this in mind we reinvented QUIPU.
As BI-experts we focused on automation of the data warehouse. But looking at this from a distance we can only conclude that a data warehouse is nothing but a set of patterns. As are data migration, big data applications, specific data transformations and so on and so forth.
Over the years we met many customers with their specific data management needs. And still every time experts tend to sit down and use the tools at hand to start building the same solution they built over and over again. Hence introducing a lot of risk to companies because of custom and divergent coding and repeating the same boring tasks they did before to achieve the same results. This is exactly where a good expert distinguishes himself from a mediocre one. By searching for means that automate these boring tasks. Leaving the complex and hence the fun stuff to the expert to solve.
That is precisely why we reinvented QUIPU. To provide a platform based on a metadata repository that can automate whatever data management challenge. Thus reducing risk by generating high quality code based on meta data that does not need testing anymore. By creating and adding custom modules together with our customers we grow the capabilities of the platform. Using templates, that customers can maintain themselves to allow for implementation of the solution in their particular application landscape.
Pattern-based model-to-model conversions and automation are a perfect match!
A brief history
2019QUIPU4
QUIPU4: A completely new web-based visual data solution generator is released!2010QUIPU
The term data warehouse automation was first coined at a Dutch event with the same name. In that same year the first data warehouse automation tool QUIPUwas released to generate data vault modeled data warehouses.2000Linstedt
Data vault modeling concept publicly released1996Kimball
Ralph Kimball publishes the book The Data Warehouse Toolkit.1992 Inmon
Bill Inmon publishes the book Building the Data Warehouse1980sDecision Support Systems
The rise of various DSS's. Also the first data warehouse architecture descriptions appear.1970sData warehouse
Bill Inmon defines and discusses the term data warehouse for the first time.1960sDimensions and facts
As part of a research project, the terms dimension and fact were developed for the first time.