{"id":495768,"date":"2023-07-18T06:52:24","date_gmt":"2023-07-18T04:52:24","guid":{"rendered":"https:\/\/www.devoteam.com\/success-story\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\/"},"modified":"2025-02-11T10:51:33","modified_gmt":"2025-02-11T09:51:33","slug":"omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform","status":"publish","type":"success-story","link":"https:\/\/devoteam.info\/en-nl\/success-story\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\/","title":{"rendered":"Omgevingsdienst gets more control on their information through new Data Platform"},"content":{"rendered":"\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#f8485e;font-size:clamp(16.293px, 1.018rem + ((1vw - 3.2px) * 0.751), 25px);\"><strong>About the Omgevingsdienst Zuidoost-Brabant<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Omgevingsdienst Zuidoost-Brabant (hereinafter &#8220;ODZOB&#8221;) is one of 29 environmental services in the Netherlands and was established in 2013 in response to the Enschede fireworks disaster, the Hemeltje fire in Volendam and the Moerdijk disaster. Environmental services deal with a wide range of activities. For municipalities, province and network partners they perform tasks in the field of licensing, supervision and enforcement, and they give advice on environmental law. Nearly 240 ODZOB employees ensure a safe and healthy physical environment. Every day again.<\/p>\n\n\n\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#f8485e;font-size:clamp(16.293px, 1.018rem + ((1vw - 3.2px) * 0.751), 25px);\"><strong>Way of working<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">ODZOB receives cases from external organizations. Think for example of a company that applies for an environmental permit or a municipality that requests that supervision be carried out somewhere. Via the requested cases the information is processed into a product: a license or an enforcement decision and thus delivered back to the chain (municipality, province or other authorities).<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full is-resized is-style-rounded wp-duotone-unset-1\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2024\/12\/Omgevingsdienst-edited-1.jpg\" alt=\"\" class=\"wp-image-23622\" width=\"458\" height=\"213\"\/><\/figure>\n\n\n\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#f8485e;font-size:clamp(16.293px, 1.018rem + ((1vw - 3.2px) * 0.751), 25px);\"><strong>The challenge<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Omgevingsdienst used an on-premise SQL environment where various sources were collected, including data from the case system, land registry, KVK data. The SQL environment was used both to extract data from the sources and to generate queries for reports. In the old way of working, a lot of information got stuck in these systems or documents were stored somewhere directly. The Environmental Department was running into data system limitations and not being able to optimally use both internal and external data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.345), 18px);\"><strong>The old data warehouse<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Several years ago, an SQL environment had been set up that collected data and made it available for reports. At that time, the SQL environment was adequate and well built. But with the new developments, it became unstructured. To extract data, 1 large table was used, with more than 100 columns. This table was used in all kinds of reports, where it was not always clear where information came from and what transformations had taken place. This made it difficult to interpret the data and determine whether it had the right quality.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In addition, there was no uniform notation defined for the data fields, there were no unambiguous keys of the different (source) objects and thus it was often not possible to link this data to other sources. Due to the size of the SQL environment, the Omgevingsdienst was unable to backup the entire table in one day.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Information exchange for receiving as well as sharing information between different partners is crucial. The desire was that data could be delivered from the data environment rather than directly from the source applications. This should make it possible to continuously and automatically feed dashboards with fresh information.<\/p>\n\n\n\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#f8485e;font-size:clamp(16.293px, 1.018rem + ((1vw - 3.2px) * 0.751), 25px);\"><strong>The solution<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Devoteam took a pragmatic approach, so that results could be achieved within a relatively short period of time. This offered the possibility to start with a defined and limited investment and lead time, after which it could be quickly evaluated whether this solution met the wishes and expectations of the Omgevingsdienst Zuidoost-Brabant.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.345), 18px);\"><strong>Migration to the cloud<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Since ODZOB already used Microsoft products within the organization, Microsoft Azure was chosen as the Cloud Provider. It was easy to integrate with the other products within the organization, including Power BI. The Omgevingsdienst migrated from an on-premise environment to the cloud platform, which brought many benefits. For example:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The process of scaling up and down of resources was easier;<\/li>\n\n\n\n<li>Automatic integration between different parts of the platform;<\/li>\n\n\n\n<li>Taking maintenance out of your hands for security and hardware;&nbsp;<\/li>\n\n\n\n<li>Being able to use Platform as a Service (PaaS) and Software as a Service (SaaS) products.&nbsp;<\/li>\n<\/ul>\n\n\n\n\t<div class=\"align wp-block-acf-quote\">\n\n\t\n\t<figure class=\"text-center\"><blockquote class=\"blockquote\"><svg width=\"49\" height=\"38\" viewBox=\"0 0 49 38\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M42.875 0C44.4995 0 46.0574 0.652728 47.206 1.81459C48.3547 2.97645 49 4.55228 49 6.1954V15.4885C49 17.1316 48.3547 18.7075 47.206 19.8693C46.0574 21.0312 44.4995 21.6839 42.875 21.6839H33.6875C33.6875 24.1486 34.6555 26.5123 36.3785 28.2551C38.1014 29.9979 40.4383 30.977 42.875 30.977H45.9375C46.7497 30.977 47.5287 31.3034 48.103 31.8843C48.6773 32.4652 49 33.2532 49 34.0747C49 34.8963 48.6773 35.6842 48.103 36.2651C47.5287 36.8461 46.7497 37.1724 45.9375 37.1724H42.875C38.8139 37.1724 34.9191 35.5406 32.0474 32.6359C29.1758 29.7313 27.5625 25.7917 27.5625 21.6839V6.1954C27.5625 4.55228 28.2078 2.97645 29.3565 1.81459C30.5051 0.652728 32.063 0 33.6875 0H42.875ZM15.3125 0C16.937 0 18.4949 0.652728 19.6435 1.81459C20.7922 2.97645 21.4375 4.55228 21.4375 6.1954V15.4885C21.4375 17.1316 20.7922 18.7075 19.6435 19.8693C18.4949 21.0312 16.937 21.6839 15.3125 21.6839H6.125C6.125 24.1486 7.09296 26.5123 8.81596 28.2551C10.5389 29.9979 12.8758 30.977 15.3125 30.977H18.375C19.1872 30.977 19.9662 31.3034 20.5405 31.8843C21.1148 32.4652 21.4375 33.2532 21.4375 34.0747C21.4375 34.8963 21.1148 35.6842 20.5405 36.2651C19.9662 36.8461 19.1872 37.1724 18.375 37.1724H15.3125C11.2514 37.1724 7.35658 35.5406 4.48493 32.6359C1.61328 29.7313 0 25.7917 0 21.6839V6.1954C0 4.55228 0.645313 2.97645 1.79397 1.81459C2.94263 0.652728 4.50055 0 6.125 0H15.3125Z\" fill=\"#3C3C3A\"\/>\n<\/svg><p>From a list factory to customized information. FastBeat provides a structured understanding of our data.<\/p><\/blockquote><figcaption class=\"blockquote-footer\">\n<div class=\"wp-block-group is-nowrap is-layout-flex wp-container-core-group-is-layout-8d39b2df wp-block-group-is-layout-flex\"><figure class=\"wp-block-image size-full is-resized is-style-rounded\"><img decoding=\"async\" src=\"https:\/\/devo2024.local\/wp-content\/uploads\/2024\/08\/nico-sienaert.jpg\" alt=\"\" class=\"wp-image-36180\" style=\"aspect-ratio:1;object-fit:cover;width:80px\"\/><\/figure>\n<div class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-6fa7971b wp-block-group-is-layout-flex\">\n\t<p class=\"has-medium-font-size wp-block-paragraph\" style=\"font-style:normal;font-weight:500\">Danielle Reijnders<\/p>\n\t\n\t<p class=\"wp-block-paragraph\">Coordinator of Team Information u0026 Research<\/p>\n\t<\/div>\n<\/div>\n<\/figcaption><\/figure>\n\t\n\t<\/div>\n\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.345), 18px);\"><strong>FastBeat Data Platform Enablement<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/nl.devoteam.com\/nl\/data-consulting-met-microsoft-technology\/\" target=\"_blank\" rel=\"noreferrer noopener\">FastBeat<\/a> is a framework, developed by Devoteam, for accelerated creation and orchestration of a Data Platform on Microsoft Azure. FastBeat uses DevOps pipelines to set up and manage the data platform. Using FastBeat, it was possible to set up a complete and integrated data platform for the Omgevingsdienst in a few days. FastBeat builds on previous implementations, providing proven and solidly built and configured environments in addition to faster implementation. These meet Microsoft&#8217;s current standards of best practices.<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image aligncenter is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2024\/12\/J_ntBI0BSKz8xbRFYcq-AGjHL8hWQVe4EYILTTcdS0ZyxwsaE1dlGdeY9bJcCrtu6h5vhdFuDW-t7cOiEjwkDEc-0y4XwnMsNQlzQ-S5mRAbLIx0AXU03-LnRG9XxgUmo2Lur8_98i0mKzTHiTlJYaM.png\" alt=\"\" width=\"721\" height=\"343\"\/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.345), 18px);\"><br><strong>Databricks Delta Lake<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Databricks Delta Lake is a combination between a Data Warehouse and a Data Lake and uses a new type of storage, delta tables, which allows data stored in a data lake to be used as if it were in a Data Warehouse. Through this Data Lake, data can be stored centrally regardless of what type of data it is (structured, semi-structured and unstructured data).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.345), 18px);\"><strong>Monitoring &amp; Security<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To meet all possible standards in terms of security and reliability of the platform, all parts of the platform are integrated with Azure&#8217;s Monitoring and Security tools.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.345), 18px);\"><strong>Implementation<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">After we had set up the new data environment, the employees had to be able to work with it themselves. Devoteam wrote a structured manual for employees and organized a number of sessions where employees learned to work with the new platform. The entire implementation from the beginning to a well-functioning data platform, where ODZOB was able to manage it themselves, was successfully realized within a few months!<\/p>\n\n\n\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#f8485e;font-size:clamp(16.293px, 1.018rem + ((1vw - 3.2px) * 0.751), 25px);\"><strong>Results<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Fewer manual tasks: time saving<\/strong> &#8211; Through FastBeat, there are fewer manual, repetitive tasks. Because different things are now automated, up-to-date information comes in from different sources.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>More in control<\/strong> &#8211; Data is traceable and more reliable. With FastBeat, Devoteam has ensured that the Omgevingsdienst is in control of the availability and performance of the data (transformations). In this way, the data is definitely no longer a &#8220;black box&#8221;.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Integration<\/strong> &#8211; With the new data platform, ODZOB has one environment for all their data needs. The environment is directly connected to all their source systems (case system, cadastre and KVK data). The data platform is fully integrated with the BI dashboard solution (Power BI) and easy to use for making analyses within an online workplace or on local devices. This allows the data to be kept centralized and up-to-date, and enables cooperative development.<\/li>\n<\/ul>\n\n\n\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#f8485e;font-size:clamp(16.293px, 1.018rem + ((1vw - 3.2px) * 0.751), 25px);\">Devoteam in the public sector<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In Devoteam you will find a reliable and experienced partner in the field of digital transformation processes, social domain issues, chain management and functional management. We provide innovative advice and customized solutions in the areas of change management, process management, training and interim management.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>About the Omgevingsdienst Zuidoost-Brabant The Omgevingsdienst Zuidoost-Brabant (hereinafter &#8220;ODZOB&#8221;) is one of 29 environmental services in the Netherlands and was established in 2013 in response to the Enschede fireworks disaster, the Hemeltje fire in Volendam and the Moerdijk disaster. Environmental services deal with a wide range of activities. For municipalities, province and network partners they [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","categories":[986,1071],"tags":[2891,2893,2297,3334,2733,2717],"industry":[],"class_list":["post-495768","success-story","type-success-story","status-publish","hentry","category-data-en-nl","category-microsoft-en-nl","tag-azure-en-nl","tag-cloud-en-nl","tag-data-en-nl","tag-integration-en-nl","tag-microsoft-en-nl","tag-netherlands-en-nl"],"acf":[],"cards":"\n\t<div class=\"single-post-card\">\n\n\t\t\n\n\t\t\n\t\t<div class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-43282307 wp-block-group-is-layout-flex\">\n\t<p style=\"font-style:normal;font-weight:700\" class=\"has-link-color wp-elements-1 wp-block-lp-post-type has-text-color has-primary-color has-small-font-size\">Success story<\/p>\n\n\t\t\n\t\t<h3 style=\"font-style:normal;font-weight:400\" class=\"wp-block-post-title has-base-font-size\"><a href=\"https:\/\/devoteam.info\/en-nl\/success-story\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\/\" target=\"_self\" >Omgevingsdienst gets more control on their information through new Data Platform<\/a><\/h3><\/div>\n\t\t\n\t<\/div>\n\n","yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.4 (Yoast SEO v28.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Omgevingsdienst gets more control on their information through new Data Platform | Devoteam<\/title>\n<meta name=\"description\" content=\"The Omgevingsdienst used an on-premise SQL environment where various sources were collected, including data from the case system, land registry, KVK data. The SQL environment was used both to extract data from the sources and to generate queries for reports. In the old way of working, a lot of information got stuck in these systems or documents were stored somewhere directly. The Environmental Department was running into data system limitations and not being able to optimally use both internal and external data.The old data warehouseSeveral years ago, an SQL environment had been set up that collected data and made it available for reports. At that time, the SQL environment was adequate and well built. But with the new developments, it became unstructured. To extract data, 1 large table was used, with more than 100 columns. This table was used in all kinds of reports, where it was not always clear where information came from and what transformations had taken place. This made it difficult to interpret the data and determine whether it had the right quality.In addition, there was no uniform notation defined for the data fields, there were no unambiguous keys of the different (source) objects and thus it was often not possible to link this data to other sources. Due to the size of the SQL environment, the Omgevingsdienst was unable to backup the entire table in one day.Information exchange for receiving as well as sharing information between different partners is crucial. The desire was that data could be delivered from the data environment rather than directly from the source applications. This should make it possible to continuously and automatically feed dashboards with fresh information.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/devoteam.info\/en-nl\/success-story\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Omgevingsdienst gets more control on their information through new Data Platform\" \/>\n<meta property=\"og:description\" content=\"The Omgevingsdienst used an on-premise SQL environment where various sources were collected, including data from the case system, land registry, KVK data. The SQL environment was used both to extract data from the sources and to generate queries for reports. In the old way of working, a lot of information got stuck in these systems or documents were stored somewhere directly. The Environmental Department was running into data system limitations and not being able to optimally use both internal and external data.The old data warehouseSeveral years ago, an SQL environment had been set up that collected data and made it available for reports. At that time, the SQL environment was adequate and well built. But with the new developments, it became unstructured. To extract data, 1 large table was used, with more than 100 columns. This table was used in all kinds of reports, where it was not always clear where information came from and what transformations had taken place. This made it difficult to interpret the data and determine whether it had the right quality.In addition, there was no uniform notation defined for the data fields, there were no unambiguous keys of the different (source) objects and thus it was often not possible to link this data to other sources. Due to the size of the SQL environment, the Omgevingsdienst was unable to backup the entire table in one day.Information exchange for receiving as well as sharing information between different partners is crucial. The desire was that data could be delivered from the data environment rather than directly from the source applications. This should make it possible to continuously and automatically feed dashboards with fresh information.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/devoteam.info\/en-nl\/success-story\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\/\" \/>\n<meta property=\"og:site_name\" content=\"Devoteam\" \/>\n<meta property=\"article:modified_time\" content=\"2025-02-11T09:51:33+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/devoteam.info\/wp-content\/uploads\/2024\/12\/tyler-lastovich-9Eheu3sIgrM-unsplash-scaled-2.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1812\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"6 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/devoteam.info\\\/en-nl\\\/success-story\\\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\\\/\",\"url\":\"https:\\\/\\\/devoteam.info\\\/en-nl\\\/success-story\\\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\\\/\",\"name\":\"Omgevingsdienst gets more control on their information through new Data Platform | Devoteam\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/devoteam.info\\\/en-nl\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/devoteam.info\\\/en-nl\\\/success-story\\\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/devoteam.info\\\/en-nl\\\/success-story\\\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/devoteam.info\\\/wp-content\\\/uploads\\\/2024\\\/12\\\/Omgevingsdienst-edited-1.jpg\",\"datePublished\":\"2023-07-18T04:52:24+00:00\",\"dateModified\":\"2025-02-11T09:51:33+00:00\",\"description\":\"The Omgevingsdienst used an on-premise SQL environment where various sources were collected, including data from the case system, land registry, KVK data. 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The SQL environment was used both to extract data from the sources and to generate queries for reports. In the old way of working, a lot of information got stuck in these systems or documents were stored somewhere directly. The Environmental Department was running into data system limitations and not being able to optimally use both internal and external data.The old data warehouseSeveral years ago, an SQL environment had been set up that collected data and made it available for reports. At that time, the SQL environment was adequate and well built. But with the new developments, it became unstructured. To extract data, 1 large table was used, with more than 100 columns. This table was used in all kinds of reports, where it was not always clear where information came from and what transformations had taken place. This made it difficult to interpret the data and determine whether it had the right quality.In addition, there was no uniform notation defined for the data fields, there were no unambiguous keys of the different (source) objects and thus it was often not possible to link this data to other sources. Due to the size of the SQL environment, the Omgevingsdienst was unable to backup the entire table in one day.Information exchange for receiving as well as sharing information between different partners is crucial. The desire was that data could be delivered from the data environment rather than directly from the source applications. This should make it possible to continuously and automatically feed dashboards with fresh information.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/devoteam.info\/en-nl\/success-story\/omgevingsdienst-gets-more-control-of-their-data-through-new-data-platform\/","og_locale":"en_US","og_type":"article","og_title":"Omgevingsdienst gets more control on their information through new Data Platform","og_description":"The Omgevingsdienst used an on-premise SQL environment where various sources were collected, including data from the case system, land registry, KVK data. The SQL environment was used both to extract data from the sources and to generate queries for reports. In the old way of working, a lot of information got stuck in these systems or documents were stored somewhere directly. The Environmental Department was running into data system limitations and not being able to optimally use both internal and external data.The old data warehouseSeveral years ago, an SQL environment had been set up that collected data and made it available for reports. At that time, the SQL environment was adequate and well built. But with the new developments, it became unstructured. To extract data, 1 large table was used, with more than 100 columns. This table was used in all kinds of reports, where it was not always clear where information came from and what transformations had taken place. This made it difficult to interpret the data and determine whether it had the right quality.In addition, there was no uniform notation defined for the data fields, there were no unambiguous keys of the different (source) objects and thus it was often not possible to link this data to other sources. Due to the size of the SQL environment, the Omgevingsdienst was unable to backup the entire table in one day.Information exchange for receiving as well as sharing information between different partners is crucial. The desire was that data could be delivered from the data environment rather than directly from the source applications. 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The SQL environment was used both to extract data from the sources and to generate queries for reports. In the old way of working, a lot of information got stuck in these systems or documents were stored somewhere directly. The Environmental Department was running into data system limitations and not being able to optimally use both internal and external data.The old data warehouseSeveral years ago, an SQL environment had been set up that collected data and made it available for reports. At that time, the SQL environment was adequate and well built. But with the new developments, it became unstructured. To extract data, 1 large table was used, with more than 100 columns. This table was used in all kinds of reports, where it was not always clear where information came from and what transformations had taken place. This made it difficult to interpret the data and determine whether it had the right quality.In addition, there was no uniform notation defined for the data fields, there were no unambiguous keys of the different (source) objects and thus it was often not possible to link this data to other sources. Due to the size of the SQL environment, the Omgevingsdienst was unable to backup the entire table in one day.Information exchange for receiving as well as sharing information between different partners is crucial. The desire was that data could be delivered from the data environment rather than directly from the source applications. 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Environmental services deal with a wide range of activities. 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