Eksempler på brug af The data warehouse på Engelsk og deres oversættelser til Dansk
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The Data Warehouse of the future is here now.
These can be created correctly thereafter in the source system and be included in the Data Warehouse after the next ETL run.
Cubes can be built above the data warehouse, for instance, with or without an SQL data mart.
These are utilised primarily at the start-up of a data warehouse project or when it is time for an upgrade orchange of the platform on which the data warehouse operates.
We aim at upgrading the Data Warehouse to Microsoft SQL Server 2016 as soon as possible.
Kompan and Kapacity have cooperated for several years;among other things, Kapacity has designed the Data Warehouse that feed Kompan's TARGIT Business Intelligence solution with data. .
The Data Warehouse uses multidimensional OLAP cubes, BIML for package generation, and it is deployed with a fully automated deployment procedure.
Instead of manually writing code orusing BIML script, the data warehouse can be modelled and built using a Data Warehouse Automation tool.
Once the Data Warehouse is in place, there is certainty for consistency in the data and business logic, performance in the queries as well as trust in a well-coordinated Business Analytics solution.
Despite Codd's warning, DAG has evolved to become the tool that represents the translation of the extract/ transform/ load(ETL)process- the original maintenance engine of the data warehouse- for Apache Spark.
Over the past 5-10 years the data warehouse has been questioned by customers, software suppliers and developers for various reasons, such as delivery times and cost.
Finally, a Master Data Management solution can be used to manage target KPIs ina Performance Management set-up, allowing users to periodically adjust these targets without changing the logic in the Data Warehouse or reports.
The data warehouse, discovered by UpGuard Director of Cyber Risk Research Chris Vickery, was hosted on a subdomain of AIQ and using a custom version of Gitlab, located at the web address gitlab. aggregateiq. com.
Part I: The data center takes form, and businesses adapt or perish Part II:A new alliance makes a daring charge on the data warehouse Part III: We interrupt this revolution: Apache Spark changes the rules of the game Part IV: The drive for synchronicity shakes the foundations of the data warehouse.
Once the Data Warehouse is in place, there is certainty for consistency in the data and business logic, performance in the queries as well as trust in a well-coordinated Business Analytics solution. Monitoring Highlighting the critical key ratios that are important for the company's business strategy ensures that everyone is focused on what really makes a difference.
This means that we must build the Data Warehouse based on a principle where metadata can define our integrations, naming and, in some cases, also our logic, so that we can replace a source system and, with only a few fixes, achieve the same data contexts in our analyses as were available before the replacement.
Using the data collected in the Central Data Warehouse ensures a faster start and an opportunity for a qualified, data-driven starting point for the company's budgets that can then be adapted to the forward-looking plans.
Data Warehouse- the cornerstone of our solutions- Kapacity A/S.
A central Data Warehouse is the cornerstone of our solutions.
Both initiatives use a subset of the statistics published by the ECB in its Statistical Data Warehouse.
Kapacity over performed compared to their own time schedule for the development of our new data warehouse.
In that reality, a new wave of digital transformation is taking place,bringing with it a concept called the“integrated data warehouse.”.
Kapacity was founded in 2008 by five ambitious partners, all with the desire to deliver world-class data warehouse and business analytics solutions.
By building a robust Data Warehouse, we ensure consistent data and the ability to make meaningful comparisons.
A data warehouse consists of the data bank itself which uses standard SQL.
A large part of the work involved in constructing a data warehouse is based on understanding all the data and the way it ties together.
A central Data Warehouse is the cornerstone of our solutions.