A company should have strong drivers to start the data management, particularly data lineage initiative. These initiatives may bring many challenges associated with the resources required. Such drivers usually play the roles of \u201ccarrot and stick\u201d simultaneously. So, a company should balance between the needs of implementing data lineage and the benefits that this implementation could deliver.<\/p>\n
There are at least four key types of business drivers that motivate companies to start a data lineage initiative:<\/p>\n
\u00b7 Compliance with legislative requirements<\/p>\n
\u00b7 Business change<\/p>\n
\u00b7 Data management initiatives<\/p>\n
\u00b7 Transparency and audit requirements<\/p>\n
Compliance with legislative requirements<\/strong><\/p>\n My professional journey to data lineage has started with investigating the Basel Committee requirements on Banking Supervision\u2018s standard number 239: \u201cPrinciples for effective risk data aggregation and risk reporting\u201d (BCBS 239 or PERDARR). Later on, I added the EU General Data Protection Regulation (GDPR), IFRS9, and TRIM (Targeted review of internal models) to this list. Some other requirements came later. Legislative requirements vary per industry. Many specialists consider data lineage the ultimate \u2018remedy\u2019 to meet these requirements. The strangest thing is that you never find the term \u201cdata lineage\u201d literally mentioned in these regulatory documents. All conclusions about the necessity of data lineage are based on careful investigation of legislation requirements and the consequent matching of these requirements to the data management ammunition, with data lineage being part of it.<\/p>\n Business Changes<\/strong><\/p>\n A company often deals with different business changes; changes in information needs and requirements, changes in application landscape, and organizational changes are examples. Impact and root-cause analysis is a tool required to perform these changes. Documented data lineage can be of great help in performing such analysis.<\/p>\n Data Management Initiatives<\/strong><\/p>\n Data quality, reference and master data management, data warehouse and business intelligence (DWH & BI), and data integration are key data management capabilities that require data lineage as input to perform their activities. The implementation of these capabilities is on the agenda of a lot of companies around the globe.<\/p>\n Transparency and audit requirements<\/strong><\/p>\n There is a growing tendency that, next to aggregated reports, supervisors require companies to provide granular reporting data – besides, especially finance and risk functions, camp with requirements to explain data origins and transformations. Data lineage is a means to assist in performing these tasks.<\/p>\n","protected":false},"excerpt":{"rendered":" A company should have strong drivers to start the data management, particularly data lineage initiative. These initiatives may bring many challenges associated with the resources required. Such drivers usually play the roles of \u201ccarrot and stick\u201d simultaneously. So, a company should balance between the needs of implementing data lineage and the benefits that this implementation […]<\/p>\n","protected":false},"author":481,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[11],"tags":[],"acf":[],"yoast_head":"\n