{"id":48970,"date":"2010-04-05T09:03:21","date_gmt":"2010-04-05T06:03:21","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=48970"},"modified":"2021-11-23T03:06:15","modified_gmt":"2021-11-23T00:06:15","slug":"whom-to-blame-for-no-success-in-data-integration","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/whom-to-blame-for-no-success-in-data-integration\/","title":{"rendered":"Whom to Blame for no Success in Data Integration?"},"content":{"rendered":"<p><center><\/p>\n<p><small>(<a href=\"https:\/\/tdwi.org\/~\/media\/TDWI\/TDWI\/Miscellaneous\/2002\/08\/TDWI_Data_Integration_Webcast%20pdf.ashx\" rel=\"noopener noreferrer\" target=\"_blank\">Featured image credit<\/a>)<\/small><\/p>\n<p><\/center><\/p>\n<p>&nbsp;<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/whom-to-blame-for-no-success-in-data-integration\/#A_growing_demand_for_data_integration\" >A growing demand for data integration<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/whom-to-blame-for-no-success-in-data-integration\/#The_sources_of_data_integration_issues\" >The sources of data integration issues<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/whom-to-blame-for-no-success-in-data-integration\/#New_challenges_ahead\" >New challenges ahead<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.altoros.com\/blog\/whom-to-blame-for-no-success-in-data-integration\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"A_growing_demand_for_data_integration\"><\/span>A growing demand for data integration<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Data integration software market shows no sign of slowing. In February 2009, Gartner predicted the 17% annual growth for the data integration software market over the next four years. What makes data integration professionals expect a high demand for their services?<\/p>\n<p>Well, now it is obvious that data is not just information stored for the sake of compliance, but that it holds a great value to corporate decision-makers. This understanding is not simply about providing a basis for sales and marketing, but also about accurate and timely data being the foundation for business performance management.<\/p>\n<p>Today, data integration has stretched far beyond basic extraction, transformation, and loading (<a href=\"https:\/\/www.altoros.com\/blog\/etl-whats-in-abbreviation\/\">ETL<\/a>). The demand for experts and software capable to cope with data integration challenges\u2014such as cleansing data and improving the data content, mapping data elements to some standard or common value, transforming data that does not meet common expected rules, and coping with the situations when these rules fail\u2014is growing as data projects become larger.<\/p>\n<p>In this process, ETL adoption is regarded as a prelude to the implementation of corporate-wide, standard business intelligence software.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/04\/ibm-bi-and-dw-data-layers.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/04\/ibm-bi-and-dw-data-layers-1024x643.png\" width=\"720\" class=\"aligncenter size-large wp-image-64952\" \/><\/a><small>ETL and data integration in the BI architecture (<a href=\"https:\/\/www.redbooks.ibm.com\/redbooks\/pdfs\/sg247788.pdf\" rel=\"noopener noreferrer\" target=\"_blank\">image credit<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"The_sources_of_data_integration_issues\"><\/span>The sources of data integration issues<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>At the same time, very often, we hear about the failures and challenges that companies face when starting data integration initiatives. So, what are the sources of these issues?<\/p>\n<div id=\"attachment_63629\" style=\"width: 160px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/11\/Noreen-Kendle1.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-63629\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/11\/Noreen-Kendle1-150x150.jpg\" width=\"150\" height=\"150\" class=\"size-thumbnail wp-image-63629\" \/><\/a><p id=\"caption-attachment-63629\" class=\"wp-caption-text\"><small>Noreen Kendle<\/small><\/p><\/div>\n<p>According to an interesting <a href=\"https:\/\/web.archive.org\/web\/20091223012411\/http:\/\/dmsblog.burtongroup.com\/data_management_strategie\/2009\/07\/is-data-integration-working-.html\" rel=\"noopener noreferrer\" target=\"_blank\">article<\/a> by data management analyst <a href=\"https:\/\/www.linkedin.com\/in\/noreen-kendle-a3440a1\/\" rel=\"noopener noreferrer\" target=\"_blank\">Noreen Kendle<\/a> I found last fall, the typical tools\/technology approach of merging data from various database systems doesn\u2019t work due to a number of things:<\/p>\n<p><b>Methodology<\/b>. Tools simply do their job on merging based on data field names or content. Assuming field names may be misleading, you can imagine the mess that may come out of it.<\/p>\n<p><b>Dimensions of time<\/b>. Time bring changes. This is true about data as well: data meaning changes over time, so two items that seem identical, but represented by different time mark may mean rather different things.<\/p>\n<p><b>Capturing data relationships<\/b>. The full meaning of data may be lost if the data is viewed individually, with no reference to its relations with other data. There should be relative meaning of data items preserved somehow in order to preserve data integrity.<\/p>\n<p>So, the better the data&#8217;s quality and structure\/relationships are, the better tools\/technology approach to data integration works. However, all this is insufficient without understanding the business meaning of data\u2014i.e., the data should be mapped to a business data model, and only then it is ready for integration.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"New_challenges_ahead\"><\/span>New challenges ahead<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>As the amount of data grows exponentially, the requirements to ETL systems get more complex. Today, ETL providers face some new challenges along with traditional data integration issues:<\/p>\n<p><strong>Scalability<\/strong>. ETL systems need to be able to process large volumes of data that intend to keep growing. Moreover, today\u2019s business reality requires getting more data in less time. So, scalable ETL is a must.<\/p>\n<p><strong>Interoperability<\/strong>. A large company\u2019s IT system comprises multiple disparate sources of business-critical data, such as databases, CRM systems, etc. These days, ETL tool should have connectivity to all those systems. Moreover, data integration between all data sources often requires complex transformations to make the data fit the formats common for this or that system.<\/p>\n<p><strong>Real-time data integration.<\/strong> This requirement is being heard more and more often. Business users want access to real-time information to make better decisions. The need for real-time data demands from ETL systems the ability to process extract-transform-load operations and gather all the data in a standard, homogeneous environment in a really short period of time.<\/p>\n<p>Finally, <strong>the cloud<\/strong>. As cloud offerings get mature and provide some beneficial solutions (especially for small and mid-sized business), companies decide to move parts of their applications to the cloud. Providing smooth connectivity to cloud systems is a today\u2019s ETL challenge, as well.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/10\/idc-cloud-challenges-2009.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/10\/idc-cloud-challenges-2009-1024x651.png\" width=\"720\" class=\"aligncenter size-large wp-image-63441\" \/><\/a><small>The challenges associated with the cloud model (<a href=\"https:\/\/web.archive.org\/web\/20101001200046\/http:\/\/blogs.idc.com\/ie\/?p=730\" rel=\"noopener noreferrer\" target=\"_blank\">image credit<\/a>)<\/small><\/center><\/p>\n<p>However, a lot of organizations still regard data integration as mostly a technological process, not taking into account how it impacts organization\u2019s long-term plans and the success (or failure) of business. Therefore, the success of data integration may require a shift in a mindset, too.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/gartner-names-approaches-to-successful-data-integration-projects\/\">Gartner Names Five Approaches to Successful Data Integration<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/building-etl-that-fits-your-business-requirements\/\">ETL Deployment: Ensuring Right Expectations<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/accelerating-business-intelligence-with-data-integration-and-data-quality\/\">Corporate Analysis and Business Intelligence Lack Data Quality<\/a><\/li>\n<\/ul>\n<hr\/>\n<p><center><small>The post is written by <a href=\"https:\/\/www.altoros.com\/blog\/author\/olga\/\">Olga Belokurskaya<\/a>; edited by <a href=\"https:\/\/www.altoros.com\/blog\/author\/alex\/\">Alex Khizhniak<\/a>.<\/small><\/center><\/p>\n","protected":false},"excerpt":{"rendered":"<\/p>\n<p>(Featured image credit)<\/p>\n<\/p>\n<p>&nbsp;<\/p>\n<p>A growing demand for data integration<\/p>\n<p>Data integration software market shows no sign of slowing. In February 2009, Gartner predicted the 17% annual growth for the data integration software market over the next four years. What makes data integration professionals expect a high demand for their services?<\/p>\n<p>Well, now it [&#8230;]<\/p>\n","protected":false},"author":81,"featured_media":62659,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[7],"tags":[960,895],"class_list":["post-48970","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-opinion","tag-data-integration","tag-research-and-development"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Whom to Blame for no Success in Data Integration? | Altoros<\/title>\n<meta name=\"description\" content=\"Explore the possible reasons for data integration initiatives failure and how growing market demands affect ETL systems requirements.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.altoros.com\/blog\/whom-to-blame-for-no-success-in-data-integration\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Whom to Blame for no Success in Data Integration? | Altoros\" \/>\n<meta property=\"og:description\" content=\"(Featured image credit) &nbsp; A growing demand for data integration Data integration software market shows no sign of slowing. In February 2009, Gartner predicted the 17% annual growth for the data integration software market over the next four years. What makes data integration professionals expect a high demand for their services? 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In February 2009, Gartner predicted the 17% annual growth for the data integration software market over the next four years. What makes data integration professionals expect a high demand for their services? 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