{"id":44898,"date":"2022-08-08T23:54:15","date_gmt":"2022-08-08T13:54:15","guid":{"rendered":"https:\/\/www.retarus.com\/au\/data-ingestion-the-first-step-towards-a-sustainable-data-strategy\/"},"modified":"2024-04-11T22:09:23","modified_gmt":"2024-04-11T12:09:23","slug":"data-ingestion-the-first-step-towards-a-sustainable-data-strategy","status":"publish","type":"post","link":"https:\/\/www.retarus.com\/au\/data-ingestion-the-first-step-towards-a-sustainable-data-strategy\/","title":{"rendered":"Data Ingestion: The First Step Towards a Secure and Sustainable Data Strategy"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"As an automated way to extract and transfer data, data ingestion helps you install a data pipeline which gives you a market advantage.","protected":false},"author":25,"featured_media":49363,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"[et_pb_section fb_built=\"1\" disabled_on=\"off|off|off\" admin_label=\"Header Light\" module_class=\"cc-bi ret_diagonal_2_light\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_color=\"off\" background_enable_image=\"off\" background_position=\"bottom_center\" bottom_divider_arrangement=\"above_content\" background_color_tablet=\"#f0607d\" background_color_phone=\"#f0607d\" background_last_edited=\"on|tablet\" background_enable_color_tablet=\"on\" background_enable_color_phone=\"on\" use_background_color_gradient_phone=\"off\" background_enable_image_tablet=\"off\" background_enable_image_phone=\"off\" locked=\"off\" collapsed=\"off\" global_colors_info=\"{}\"][et_pb_row column_structure=\"3_5,2_5\" admin_label=\"Row \u2013 Gradient und padding in der Column\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_image=\"https:\/\/www.retarus.com\/de\/wp-content\/uploads\/sites\/2\/2022\/08\/header_image2-data_ingestion.jpg\" global_colors_info=\"{}\"][et_pb_column type=\"3_5\" _builder_version=\"4.16\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text admin_label=\"Header \" module_class=\"smaller\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
Data Ingestion describes the automated extraction, structuring, storage, and transfer of data. This process makes it possible to install a smooth data pipeline. The preparation of heterogeneous data into a structured, cloud-based data management system enables it to be analyzed automatically in real time, offering a decisive market advantage. <\/p>\r\n
With its Intelligent Capture Services<\/b>, Retarus provides an essential data source for data ingestion. The services enable companies to digitize all business communications, make them available in a structured form in the required format and thus automate end-to-end workflows.<\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"2_5\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_image=\"https:\/\/www.retarus.com\/de\/wp-content\/uploads\/sites\/2\/2022\/08\/header_image2-data_ingestion.jpg\" global_colors_info=\"{}\"][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\"1\" admin_label=\"Von der unstrukturierten Quelle zum cloudbasierten Datenmanagementsystem: Das ist Data Ingestion \" module_class=\" cc-bi ret_service-toggles slim ret_padding_100-0\" _builder_version=\"4.17.6\" background_color=\"#FFFFFF\" bottom_divider_color=\"#FFFFFF\" bottom_divider_height=\"80px\" global_colors_info=\"{}\"][et_pb_row column_structure=\"2_3,1_3\" column_padding_mobile=\"on\" _builder_version=\"4.17.4\" max_width=\"100%\" custom_margin=\"||||false|false\" custom_padding=\"||0px||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"2_3\" module_class=\"gdpr\" _builder_version=\"4.16\" custom_padding=\"|||\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][et_pb_text admin_label=\"Intro Headline\" _builder_version=\"4.17.6\" _module_preset=\"default\" max_width=\"100%\" custom_margin=\"||||false|false\" custom_padding=\"||||false|false\" global_colors_info=\"{}\"]From an Unstructured Source to a Cloud-Based Data Management System: This Is Data Ingestion<\/h2>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"1_3\" _builder_version=\"4.16\" background_enable_color=\"off\" custom_padding=\"|||\" custom_css_main_element=\"margin-left:-30px;\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_2,1_2\" use_custom_gutter=\"on\" gutter_width=\"4\" make_equal=\"on\" column_padding_mobile=\"on\" _builder_version=\"4.17.6\" max_width=\"100%\" custom_margin=\"||||false|false\" custom_padding=\"0px||||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"1_2\" _builder_version=\"4.16\" custom_padding=\"|||\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][et_pb_text admin_label=\"Intro Text\" _builder_version=\"4.17.6\" _module_preset=\"default\" max_width_tablet=\"90%\" max_width_phone=\"90%\" max_width_last_edited=\"on|desktop\" global_colors_info=\"{}\"]
Data ingestion describes a process in which large volumes of data are imported from various sources and merged into a storage medium. This target medium is usually a cloud-based or locally installed ERP system. However, the data can also be fed into a data warehouse<\/b>, a data mart<\/b>, or a data lake<\/b>. <\/p>\r\n
In order to create added value, the data from these storage mediums must be easy to retrieve, use, and analyze. It must also be structured to create a powerful data pipeline. Special data wrangling tools are required for this structuring. In summary, data ingestion involves digitizing unstructured data, analyzing it, extracting it, structuring it, storing it, and processing it on a target medium.<\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"1_2\" _builder_version=\"4.16\" background_enable_color=\"off\" custom_padding=\"|||\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][et_pb_accordion _builder_version=\"4.17.6\" _module_preset=\"default\" toggle_level=\"h3\" global_colors_info=\"{}\"][et_pb_accordion_item title=\"Data warehouse \" open=\"on\" _builder_version=\"4.17.6\" _module_preset=\"default\" custom_margin=\"0px||||false|false\" global_colors_info=\"{}\"]The term data warehouse refers to a central database system that can be used by companies for analysis purposes. This system collects and stores important data from various data sources and supplies them to downstream systems. The advantage of a data warehouse is that it provides a global view of data from very different data sets.[\/et_pb_accordion_item][et_pb_accordion_item title=\"Data mart \" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\" open=\"off\"]A data mart is a subject-oriented database. Often but not always, it is a sub-segment of a data warehouse. However, while data warehouses contain all of a company's information, data marts only meet the needs of specific business functions or departments.[\/et_pb_accordion_item][et_pb_accordion_item title=\"Data lakes \" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\" open=\"off\"]Data lakes are large pools of raw data for which no use has yet been determined. These data lakes can contain both structured and unstructured data in large quantities for subsequent analysis. In contrast to a data warehouse, which transfers collected data directly into structures and formats, a data lake allows for data to also be stored in its raw format.[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\"1\" admin_label=\"Echtzeit oder Batches: Jede Form der Data Ingestion hat Vorteile\" module_class=\"ret_padding_100-0 cc-fax\" _builder_version=\"4.17.6\" background_color=\"#FFFFFF\" use_background_color_gradient=\"on\" background_color_gradient_stops=\"#f3f5f7 0%|#ffffff 100%\" bottom_divider_color=\"#FFFFFF\" bottom_divider_height=\"80px\" global_colors_info=\"{}\"][et_pb_row column_structure=\"2_3,1_3\" column_padding_mobile=\"on\" _builder_version=\"4.17.1\" max_width=\"100%\" global_colors_info=\"{}\"][et_pb_column type=\"2_3\" module_class=\"gdpr\" _builder_version=\"4.16\" custom_padding=\"|||\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][et_pb_text admin_label=\"Intro Headline\" module_id=\"intro\" _builder_version=\"4.17.6\" _module_preset=\"default\" max_width=\"100%\" custom_margin=\"||0px||false|false\" global_colors_info=\"{}\"]
There are currently three possible approaches to successful ingestion: Real-time ingestion, batching data ingestion, and micro-batching. Depending on project constraints and data sources, any of these options may be the optimal data strategy.<\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"2_5\" _builder_version=\"4.16\" background_enable_color=\"off\" custom_padding=\"|||\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_3,1_3,1_3\" use_custom_gutter=\"on\" gutter_width=\"4\" _builder_version=\"4.17.6\" _module_preset=\"default\" max_width=\"100%\" custom_padding=\"0px||||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"1_3\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb title=\"Real-Time Data Ingestion\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]Real-time data ingestion, also known as stream ingestion, imports each data element as it becomes available. This means that each data element is processed as an individual object. This type of data ingestion is very costly, but is especially worthwhile for analytics that need to be consistently up-to-date. Real-time data ingestion is the only solution for applications that rely on real-time data. For example, real-time data processing is essential for stock market trading.[\/et_pb_blurb][\/et_pb_column][et_pb_column type=\"1_3\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb title=\"Batch Data Ingestion\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]Batch data ingestion is the most common type of data ingestion. Here, source data is collected at fixed intervals and grouped according to defined criteria. This method is less expensive and therefore useful for companies that collect specific data on a daily basis and do not need to make decisions in real time.[\/et_pb_blurb][\/et_pb_column][et_pb_column type=\"1_3\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb title=\"Micro-Batching\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]As the name suggests, micro-batching is the intermediate stage between real-time data ingestion and batch data ingestion. Although the data is also divided into groups, it is imported in much smaller steps. It is not processed individually; the transfer time is much shorter than for large batches.[\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\"1\" disabled_on=\"off|off|off\" admin_label=\"Data Ingestion vs. ETL\" module_class=\"cc-bi ret_diagonal_1_light \" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_color=\"off\" background_enable_image=\"off\" background_position=\"center_right\" bottom_divider_arrangement=\"above_content\" locked=\"off\" collapsed=\"off\" global_colors_info=\"{}\"][et_pb_row column_structure=\"3_5,2_5\" admin_label=\"Image in der Column\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_image=\"off\" global_colors_info=\"{}\"][et_pb_column type=\"3_5\" _builder_version=\"4.16\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text admin_label=\"Text\" _builder_version=\"4.17.6\" _module_preset=\"default\" max_width=\"90%\" global_colors_info=\"{}\"]
Data ingestion and ETL, or extract, transform, and load<\/i>, are very similar processes, but they differ in their goal. Data ingestion extracts and structures data to prepare it for an application that requires a specific format. For this, the data sources do not need to be linked to the target.<\/p>\r\n
ETL is different. This specific process primarily refers to data preparation for data warehouses and data lakes. Its focus is on long-term storage for use in business intelligence (BI) and other analytics. ETL is therefore also a data ingestion process, but it involves not only the extraction of data and its transfer, but also the transformation of the data before it is sent to its destination.[\/et_pb_text][\/et_pb_column][et_pb_column type=\"2_5\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_image=\"https:\/\/www.retarus.com\/de\/wp-content\/uploads\/sites\/2\/2022\/08\/image-data_ingestion.jpg\" global_colors_info=\"{}\"][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\"1\" admin_label=\"Die Vorteile der Data Ingestion\" module_class=\"ret_padding_100-0 ret_service-toggles cc-bi\" _builder_version=\"4.17.6\" background_enable_color=\"off\" global_colors_info=\"{}\"][et_pb_row column_structure=\"3_5,2_5\" column_padding_mobile=\"on\" module_class=\"cc-fax\" _builder_version=\"4.17.4\" max_width=\"100%\" custom_padding=\"||0px||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"3_5\" _builder_version=\"4.16\" custom_padding=\"|||\" global_colors_info=\"{}\" custom_padding__hover=\"|||\"][et_pb_text admin_label=\"Text\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
Data ingestion offers several advantages that can give users the edge in highly competitive markets.<\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"2_5\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_2,1_2\" _builder_version=\"4.17.1\" _module_preset=\"default\" max_width=\"100%\" custom_padding=\"0px||||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"1_2\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb use_icon=\"on\" font_icon=\"\ue052||divi||400\" icon_color=\"RGBA(255,255,255,0)\" icon_placement=\"left\" image_icon_width=\"25px\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
One of the most important benefits of ingestion is the immediate availability of information. Data that was previously stored locally in various locations can be accessed anytime and anywhere through centralized, cloud-based storage. With the help of defined authorizations, departments and functional areas can access precisely the data they need.<\/p>[\/et_pb_blurb][\/et_pb_column][et_pb_column type=\"1_2\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb use_icon=\"on\" font_icon=\"\ue052||divi||400\" icon_color=\"RGBA(255,255,255,0)\" icon_placement=\"left\" image_icon_width=\"25px\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
Data integration and ingestion simplify analysis, especially when combined with an ETL solution and related standard formatting. Data is easier to process thanks to the reduced complexity. Pipelines can deliver data to the data warehouse immediately and completely automatically. <\/p>[\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_2,1_2\" _builder_version=\"4.17.1\" _module_preset=\"default\" max_width=\"100%\" custom_padding=\"0px||||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"1_2\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb use_icon=\"on\" font_icon=\"\ue052||divi||400\" icon_color=\"RGBA(255,255,255,0)\" icon_placement=\"left\" image_icon_width=\"25px\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
Together with an intelligent capture service, data capture tools can also process unstructured data formats. Automated processing of letters, PDFs received by email, or faxes is therefore no longer a problem. This flexibility enables smooth processes in all areas.<\/p>[\/et_pb_blurb][\/et_pb_column][et_pb_column type=\"1_2\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_blurb use_icon=\"on\" font_icon=\"\ue052||divi||400\" icon_color=\"RGBA(255,255,255,0)\" icon_placement=\"left\" image_icon_width=\"25px\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
Various analysis tools provide valuable BI insights from the multitude of data sources. With the help of processed data, problems and opportunities can be quickly identified and better decisions can be made. <\/p>[\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\"1\" disabled_on=\"off|off|off\" admin_label=\"So meistern Unternehmen die Herausforderungen von Data Ingestion - Desktop\" module_class=\"ret_padding_100-0 cc-bi \" _builder_version=\"4.17.6\" _module_preset=\"default\" background_color=\"#F3F5F7\" use_background_color_gradient=\"on\" background_color_gradient_stops=\"#f3f5f7 0%|#ffffff 100%\" global_colors_info=\"{}\"][et_pb_row column_structure=\"3_5,2_5\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_color=\"off\" max_width=\"100%\" custom_padding=\"||0px||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"3_5\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"]
These are the challenges faced by companies who are looking to establish data pipelines: <\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"2_5\" _builder_version=\"4.17.1\" _module_preset=\"default\" global_colors_info=\"{}\"][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_2,1_2\" use_custom_gutter=\"on\" gutter_width=\"4\" module_class=\"ret_service-toggles slim\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_color=\"off\" max_width=\"100%\" global_colors_info=\"{}\"][et_pb_column type=\"1_2\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_toggle title=\"Compliance\" _builder_version=\"4.17.6\" _module_preset=\"default\" title_level=\"h3\" global_colors_info=\"{}\"]
The most important aspects when dealing with sensitive business data are data security and protection. In data ingestion, data is made available at several points in the data pipeline. With its Intelligent Capture Services<\/b>, Retarus supports companies in meeting local and global data protection and security requirements at all times: Retarus' cloud services are fully GDPR-compliant and meet other domestic and international security and compliance requirements such as EU\u00a0Directive\u00a095\/46\/EC, ISAE\u00a03402, and SOC\u00a01 and SOC\u00a02\u00a0Type\u00a0II.<\/p>[\/et_pb_toggle][et_pb_toggle title=\"Cost\" _builder_version=\"4.17.6\" _module_preset=\"default\" title_level=\"h3\" global_colors_info=\"{}\"]
As data volumes grow, so does the need for more storage systems and servers. These are expensive and costly to maintain because of data security and privacy regulations. However, this is only an issue when using on-premises providers. <\/p>[\/et_pb_toggle][\/et_pb_column][et_pb_column type=\"1_2\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_toggle title=\"Data Quality\" _builder_version=\"4.17.6\" _module_preset=\"default\" title_level=\"h3\" global_colors_info=\"{}\"]
Keeping data quality high is particularly challenging. Retarus\u2019 Intelligent Capture <\/b> solution correctly recognizes up to 98\u00a0percent of source data with its powerful Intelligent Document Recognition (IDR) feature, which uses multiple OCR engines. The addition of human-in-the-loop offers a recognition rate of up to 100\u00a0percent. This is how Retarus creates optimal conditions for the smooth, automated further processing of digitized data.<\/p>[\/et_pb_toggle][et_pb_toggle title=\"Fragmentation and Data Integration\" _builder_version=\"4.17.6\" _module_preset=\"default\" title_level=\"h3\" global_colors_info=\"{}\"]
Data ingestion is often problematic because overlaps occur when different business units access the same source. Vendors also fail to integrate different third-party sources into one data pipeline.<\/p>[\/et_pb_toggle][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_2,1_2\" use_custom_gutter=\"on\" gutter_width=\"4\" make_equal=\"on\" disabled_on=\"on|on|on\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_color=\"off\" max_width=\"100%\" disabled=\"on\" global_colors_info=\"{}\"][et_pb_column type=\"1_2\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text admin_label=\"Text\" module_class=\"ret_sep-challenges\" _builder_version=\"4.17.6\" _module_preset=\"default\" custom_css_before=\"content: url(%22data:image\/svg+xml,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' width='48' height='48' viewBox='0 0 48 48'%3E%3Ctitle%3Epaper-diploma%3C\/title%3E%3Cg fill='%2391c159'%3E%3Cpath fill='%2391c159' d='M13,40v0.5c0,3.584-2.416,6.5-6,6.5c3.976,0,30.682,0,31,0c2.761,0,5-2.239,5-5v-2H13z'%3E%3C\/path%3E%3Cpath d='M38,24c-2.253,0-4.326-0.758-6-2.019V31c0,0.36,0.194,0.693,0.507,0.87 c0.313,0.178,0.698,0.174,1.007-0.013L38,29.166l4.485,2.691c0.308,0.186,0.695,0.191,1.007,0.013C43.806,31.692,44,31.36,44,31 v-9.019C42.326,23.242,40.253,24,38,24z'%3E%3C\/path%3E%3Cpath fill='%2391c159' d='M31.52,33.609C30.583,33.08,30,32.079,30,31V19.974c-1.25-1.669-2-3.733-2-5.975c0-5.514,4.486-10,10-10V2 c0-0.552-0.448-1-1-1H3C2.448,1,2,1.448,2,2v38.5C2,42.985,4.015,45,6.5,45s4.5-2.015,4.5-4.5V38h27v-6.502l-3.457,2.074 C33.621,34.129,32.461,34.143,31.52,33.609z M19,29h-9c-0.552,0-1-0.448-1-1s0.448-1,1-1h9c0.552,0,1,0.448,1,1S19.552,29,19,29z M23,21H10c-0.552,0-1-0.448-1-1s0.448-1,1-1h13c0.552,0,1,0.448,1,1S23.552,21,23,21z M23,13H10c-0.552,0-1-0.448-1-1s0.448-1,1-1 h13c0.552,0,1,0.448,1,1S23.552,13,23,13z'%3E%3C\/path%3E%3Ccircle cx='38' cy='14' r='8'%3E%3C\/circle%3E%3C\/g%3E%3C\/svg%3E%22);\" locked=\"off\" global_colors_info=\"{}\"]
The most important aspects when dealing with sensitive business data are probably data security and data protection. In data ingestion, data is made available at several points in the data pipeline. With its Intelligent Capture Services<\/b>, Retarus supports companies in meeting local and global data protection and data security requirements at all times: Retarus' cloud services are fully GDPR-compliant and meet other national and international security and compliance requirements such as EU\u00a0Directive\u00a095\/46\/EC, ISAE\u00a03402 and SOC\u00a01 and SOC\u00a02\u00a0Type\u00a0II.<\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"1_2\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text admin_label=\"Text\" module_class=\"ret_sep-challenges\" _builder_version=\"4.17.6\" _module_preset=\"default\" custom_css_before=\"content: url(%22data:image\/svg+xml,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' width='48' height='48' viewBox='0 0 48 48'%3E%3Ctitle%3Efolder-check%3C\/title%3E%3Cg fill='%2391c159'%3E%3Cpath d='M46,11H23.555L18.848,3.47A1,1,0,0,0,18,3H2A1,1,0,0,0,1,4V40a5.006,5.006,0,0,0,5,5H42a5.006,5.006,0,0,0,5-5V12A1,1,0,0,0,46,11ZM32.707,22.707l-12,12a1,1,0,0,1-1.414,0l-4-4a1,1,0,0,1,1.414-1.414L20,32.586,31.293,21.293a1,1,0,0,1,1.414,1.414Z' fill='%2391c159'%3E%3C\/path%3E%3C\/g%3E%3C\/svg%3E%22);\" locked=\"off\" global_colors_info=\"{}\"]Data Quality<\/h3>\r\n
Keeping data quality high is particularly challenging. Retarus\u2019 Intelligent Capture<\/b> solution correctly recognizes up to 98\u00a0percent of source data with its powerful Intelligent Document Recognition (IDR) feature, which uses multiple OCR engines. The addition of human-in-the-loop offers a recognition rate of up to 100\u00a0percent. This is how Retarus creates optimal conditions for the smooth automated further processing of digitized data.<\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\"1_2,1_2\" use_custom_gutter=\"on\" gutter_width=\"4\" disabled_on=\"on|on|on\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_enable_color=\"off\" max_width=\"100%\" disabled=\"on\" global_colors_info=\"{}\"][et_pb_column type=\"1_2\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text admin_label=\"Text\" module_class=\"ret_sep-challenges\" _builder_version=\"4.17.6\" _module_preset=\"default\" custom_css_before=\"content: url(%22data:image\/svg+xml,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' width='48' height='48' viewBox='0 0 48 48'%3E%3Ctitle%3Ecoins%3C\/title%3E%3Cg fill='%2391c159'%3E%3Cpath fill='%2391c159' d='M14,2C7.159,2,2,3.72,2,6s5.159,4,12,4s12-1.72,12-4S20.841,2,14,2z'%3E%3C\/path%3E%3Cpath d='M34,40c-4.412,0-9.327-0.735-12-2.612V42c0,2.28,5.159,4,12,4s12-1.72,12-4v-4.612 C43.327,39.265,38.412,40,34,40z'%3E%3C\/path%3E%3Cpath d='M34,32c-4.412,0-9.327-0.735-12-2.612V34c0,2.28,5.159,4,12,4s12-1.72,12-4v-4.612 C43.327,31.265,38.412,32,34,32z'%3E%3C\/path%3E%3Cpath d='M34,24c-4.412,0-9.327-0.735-12-2.612V26c0,2.28,5.159,4,12,4s12-1.72,12-4v-4.612 C43.327,23.265,38.412,24,34,24z'%3E%3C\/path%3E%3Cpath d='M34,14c-6.841,0-12,1.72-12,4s5.159,4,12,4s12-1.72,12-4S40.841,14,34,14z'%3E%3C\/path%3E%3Cpath fill='%2391c159' d='M14,18c2.242,0,4.297-0.188,6.056-0.516c0.324-2.281,2.758-3.737,5.944-4.569V9.388 C23.327,11.265,18.412,12,14,12S4.673,11.265,2,9.388V14C2,16.28,7.159,18,14,18z'%3E%3C\/path%3E%3Cpath fill='%2391c159' d='M14,26c2.218,0,4.254-0.183,6-0.505v-5.988C18.062,19.841,15.984,20,14,20c-4.412,0-9.327-0.735-12-2.612V22 C2,24.28,7.159,26,14,26z'%3E%3C\/path%3E%3Cpath fill='%2391c159' d='M14,34c2.218,0,4.254-0.183,6-0.505v-5.988C18.062,27.841,15.984,28,14,28c-4.412,0-9.327-0.735-12-2.612V30 C2,32.28,7.159,34,14,34z'%3E%3C\/path%3E%3Cpath fill='%2391c159' d='M20,35.507C18.062,35.841,15.984,36,14,36c-4.412,0-9.327-0.735-12-2.612V38c0,2.28,5.159,4,12,4 c2.218,0,4.254-0.183,6-0.505V35.507z'%3E%3C\/path%3E%3C\/g%3E%3C\/svg%3E%22);\" locked=\"off\" global_colors_info=\"{}\"]Cost<\/h3>\r\n
As data volumes grow, so does the need for more storage systems and servers. These are expensive and costly to maintain because of data security and privacy regulations. However, this is only an issue when using on-premises providers. <\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\"1_2\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text admin_label=\"Text\" module_class=\"ret_sep-challenges\" _builder_version=\"4.17.6\" _module_preset=\"default\" custom_css_before=\"content: url(%22data:image\/svg+xml,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' width='48' height='48' viewBox='0 0 48 48'%3E%3Ctitle%3Eapi%3C\/title%3E%3Cg fill='%2391c159'%3E%3Cpath d='M17,24a7,7,0,0,1,14,0H47V21a1,1,0,0,0-.917-1L40.4,19.529a16.739,16.739,0,0,0-1.641-3.956l3.691-4.362a1,1,0,0,0-.056-1.353L38.142,5.615a1,1,0,0,0-1.353-.056l-4.361,3.69A16.837,16.837,0,0,0,28.471,7.6L28,1.917A1,1,0,0,0,27,1H21a1,1,0,0,0-1,.917L19.529,7.6a16.739,16.739,0,0,0-3.956,1.641L11.211,5.554a1,1,0,0,0-1.353.056L5.615,9.858a1,1,0,0,0-.056,1.353l3.69,4.361A16.837,16.837,0,0,0,7.6,19.529L1.917,20A1,1,0,0,0,1,21v3Z' fill='%2391c159'%3E%3C\/path%3E%3Cpath d='M10,26v8.586L6.286,38.3A2.969,2.969,0,0,0,5,38a3,3,0,1,0,3,3,2.969,2.969,0,0,0-.3-1.286l4.007-4.007A1,1,0,0,0,12,35V26Z'%3E%3C\/path%3E%3Cpath d='M30,42.184V26H28V42.184a3,3,0,1,0,2,0Z'%3E%3C\/path%3E%3Cpath d='M20,37.184V26H18V37.184a3,3,0,1,0,2,0Z'%3E%3C\/path%3E%3Cpath d='M43,38a2.969,2.969,0,0,0-1.286.3L38,34.586V26H36v9a1,1,0,0,0,.293.707L40.3,39.714A2.969,2.969,0,0,0,40,41a3,3,0,1,0,3-3Z'%3E%3C\/path%3E%3C\/g%3E%3C\/svg%3E%22);\" locked=\"off\" global_colors_info=\"{}\"]
Data ingestion is often problematic because overlaps occur when different business units access the same source. Vendors also fail to integrate different third-party sources into one data pipeline.<\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=\"1\" admin_label=\"So l\u00f6st Retarus die Datenprobleme seiner Kunden\" module_class=\"ret_padding_100-0 cc-bi ret_diagonal_1_light\" _builder_version=\"4.17.6\" _module_preset=\"default\" background_color=\"#FFFFFF\" global_colors_info=\"{}\"][et_pb_row column_structure=\"3_5,2_5\" _builder_version=\"4.17.6\" _module_preset=\"default\" max_width=\"100%\" custom_padding=\"0px||||false|false\" global_colors_info=\"{}\"][et_pb_column type=\"3_5\" _builder_version=\"4.17.6\" _module_preset=\"default\" global_colors_info=\"{}\"][et_pb_text _builder_version=\"4.17.6\" _module_preset=\"default\" max_width=\"90%\" global_colors_info=\"{}\"]
Retarus offers more than just a SAAS solution. With its Managed Service, this enterprise cloud provider keeps the IT department's workload to an absolute minimum. Thanks to professional workshops focused on process improvement and support in connecting new customers, user tasks are kept to a minimum and important resources are spared. <\/p>\r\n