ICELAND
Landsbankinn needed to streamline its data infrastructure and integrate more than 45 data sources , so implemented a logical data warehouse using the Denodo Platform . Davíð Jóhannsson , Head of Information Intelligence at Landsbankinn , said that at the heart of the project was the company ’ s desire to create a data sharing culture throughout the organisation . The Denodo solution helped it to achieve a consistent view across all data silos and today the entire bank is processing data from one place .
LANDSBANKINN LEVERAGED TO ENABLE SELF-SERVICE AN AND A DATA SHARING CULTU
Colourful Icelandic houses in Stykkisholmur , Iceland
Our team used the Denodo Platform – a data integration and data management solution built on data virtualisation – to build a logical data warehouse .
Landsbankinn hf . is one of the largest financial institutions in Iceland . It was founded in 2008 and is the successor to Landsbanki Íslands , established in 1886 . Its largest shareholder is the Icelandic State Treasury ( 98,2 %). It boasts 40 % of the retail and 32 % of the corporate banking market share in Iceland . Landsbankinn wanted to accelerate its key operational and BI reporting capabilities and provide realtime data for informed decision-making across all kinds of users in the organisation . To streamline its data infrastructure and integrate more than 45 data sources , Landsbankinn implemented a logical data warehouse using the Denodo Platform .
Business need
Before implementing a logical data warehouse , Landsbankinn had a large number of data sources and three main reporting platforms for reporting including general reporting , risk reporting and KPI reporting to top management and board . The total number of data sources at Landsbankinn is around 45 , including five Oracle traditional databases , two data warehouses and around 10 Microsoft SQL Server databases . On top of this , flat files , Excel files , XML files , APIs from internal and external data sources are also used . Despite having traditional BI and a data warehouse in place , users were often not able to find and access the data they needed . Business rules and logics were scattered , creating trouble for obtaining the lineage of the data . The large , extensive query points and business objects made the situation worse . Also , access controls restricted access to a database , or certain columns of the database , making it arduous to identify the problem .
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