{"id":31513,"date":"2017-12-08T08:00:29","date_gmt":"2017-12-08T07:00:29","guid":{"rendered":"http:\/\/e3mag.com\/?p=31513"},"modified":"2025-07-12T13:03:00","modified_gmt":"2025-07-12T11:03:00","slug":"master-data-management-garbage-hana","status":"publish","type":"post","link":"https:\/\/e3mag.com\/en\/master-data-management-garbage-hana\/","title":{"rendered":"Master Data Management\u2014Garbage in and Garbage out"},"content":{"rendered":"

According to German consultants L\u00fcnendonk, around 85 percent of firms have a problem with their master data. What has been known for years in the business intelligence environment is surfacing in digital transformation. Firms must prepare themselves for digital transformation in a process-oriented way.<\/p>\n

That includes ensuring they have high-quality master data. New possibilities (e.g. machine learning) can play an active role in the process and ensure the generation of high quality data from the very outset. Such an intervention in business processes however must be desired by the firms. Although those who don\u2019t will lose out in a few years\u2019 time.<\/p>

\"Fullsize\"<\/a><\/div>\n

Two current examples<\/h3>\n

Imagine a situation where your matching algorithm automatically writes to a customer who is not even the intended recipient because the data is not complete or up-to-date. Yet how should the algorithm know what \u201ccomplete \u201cand up-to-date\u201d related to the customer\u2019s data really means? The cost incurred through the unnecessary loss of time (sending emails, making follow-up telephone calls, etc.) is one thing, but the real embarrassment is writing to the wrong customer in the first place.<\/p>\n

Imagine that on account of an automatic algorithm you decide in favor of a supplier whose data are likewise incomplete and not up-to-date like in example 1, or were even entered incorrectly (terms and conditions, delivery reliability, legal requirements, etc.). Once the order has been placed, it\u2019s difficult to withdraw. Besides the effort entailed in cancelling the order, more than anything your credibility as a customer will suffer.<\/p>\n

\"Joern<\/a><\/p>\n

Intervention in business processes<\/h3>\n

To improve the quality of master data, it is now possible to intervene in business processes especially in an SAP environment using the Hana platform. The advantage is that with Hana-based master data maintenance, options offered by matching algorithms can be used toy signal to the person processing the data whether an input is correct or incorrect, or to a certain degree of probability is correct or incorrect.<\/p>\n

In a Hana technology environment, it is possible to determine on the basis of already existing data what correct or incorrect means. How high the degree of accuracy of the master data is as a whole must be evaluated, defined and if need be, clarified in advance. As data is added, the accuracy (= consistency and completeness as well as current validity and semantics) of the data will gradually increase and thus improve the basis for further decisions.<\/p>\n

This process applies machine learning methodology\u2014learning from incoming data. However, the process also places demands on the person handling the data. He is ultimately responsible for ensuring the high quality of data! But with machine learning, he is given a tool to successfully carry out the required visual check.<\/p>\n

Why Hana now?<\/h3>\n

A decisive step towards improving the quality of master data is interactively influencing data input by entering default values and\/or probability statements. The empirical values gained from the machine learning approach must be available in real time. An evaluation of empirical values in \u201cadjoining\u201d data management systems (Hadoop etc.) is not helpful for real-time processing.<\/p>\n

The empirical values (not necessarily the entire data pool from which these values were extracted) should thus be right there where they are needed during runtime, i.e. directly in the database of the operative system. To use these possibilities within the SAP Hana platform, licensing requirements have to be met. In any case, it is an investment \u2013 but one that is worth it. Even today, not only about five to ten percent of the entire time spent on rectifying master data errors can be saved, but the knowledge based on modern algorithms can be reliably transformed into a real gain \u2013 right now and well ahead of market competitors.<\/p>\n

\"Detect<\/a><\/p>","protected":false},"excerpt":{"rendered":"

While experts are still musing over the accuracy of matching or forecast algorithms, the quality of the underlying master data is lagging behind. So on what basis should business-critical forecasts be made? <\/p>","protected":false},"author":1069,"featured_media":31515,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"pmpro_default_level":"","footnotes":""},"categories":[5,19171],"tags":[798,65,662,480,3491,610],"coauthors":[24792],"class_list":["post-31513","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-it-management","category-mag-1712","tag-hadoop","tag-hana","tag-luenendonk","tag-machine-learning","tag-sap-hana","tag-stammdaten","pmpro-has-access"],"acf":[],"featured_image_urls_v2":{"full":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"thumbnail":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-150x150.jpg",150,150,true],"medium":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",400,215,false],"medium_large":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-768x413.jpg",768,413,true],"large":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"image-100":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-100x54.jpg",100,54,true],"image-480":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-480x258.jpg",480,258,true],"image-640":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-640x344.jpg",640,344,true],"image-720":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-720x387.jpg",720,387,true],"image-960":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-960x516.jpg",960,516,true],"image-1168":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"image-1440":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"image-1920":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"1536x1536":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"2048x2048":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"trp-custom-language-flag":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",18,10,false],"bricks_large_16x9":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"bricks_large":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"bricks_large_square":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",1000,538,false],"bricks_medium":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",600,323,false],"bricks_medium_square":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299.jpg",600,323,false],"profile_24":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-24x24.jpg",24,24,true],"profile_48":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-48x48.jpg",48,48,true],"profile_96":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-96x96.jpg",96,96,true],"profile_150":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-150x150.jpg",150,150,true],"profile_300":["https:\/\/e3mag.com\/wp-content\/uploads\/2017\/11\/shutterstock_467490299-300x300.jpg",300,300,true]},"post_excerpt_stackable_v2":"

W\u00e4hrend sich Experten noch \u00fcber die Genauigkeit von Matching- oder Vorhersage-Algorithmen Gedanken machen, hinkt die Qualit\u00e4t der zugrunde liegenden Stammdaten hinterher. Auf welcher Grundlage sollen dann also gesch\u00e4ftsentscheidende Vorhersagen getroffen werden? <\/p>\n","category_list_v2":"IT-Management<\/a>, MAG 17-12<\/a>","author_info_v2":{"name":"J\u00f6rn D\u00f6ring, Detect Value","url":"https:\/\/e3mag.com\/en\/author\/joern-doering\/"},"comments_num_v2":"0 comments","_links":{"self":[{"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/posts\/31513","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/users\/1069"}],"replies":[{"embeddable":true,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/comments?post=31513"}],"version-history":[{"count":4,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/posts\/31513\/revisions"}],"predecessor-version":[{"id":152396,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/posts\/31513\/revisions\/152396"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/media\/31515"}],"wp:attachment":[{"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/media?parent=31513"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/categories?post=31513"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/tags?post=31513"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/e3mag.com\/en\/wp-json\/wp\/v2\/coauthors?post=31513"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}