Ebooks

Data Integration and Governance for the Modern Enterprise 2021

Issue link: https://read.uberflip.com/i/1404248

Contents of this Issue

Navigation

Page 1 of 14

Sponsored Content 20 AUGUST/SEPTEMBER 2021 | DBTA Data flowing in from an abundance of sources brings many challenges. The tasks associated with managing data in a variety of formats and contexts can be overwhelming. In addition, there's the need to ensure that data is timely and sources are trustworthy. In other words, data integration has become everybody's job. There are three main business considerations when taking in the data needed for today's digital initiatives— that the data can support real-time or near-real-time digital business initiatives, that it meets compliance standards, and that it is trustworthy and up-to-date for business purposes. In the process, data management itself is changing. It's no longer about standing up databases and populating data warehouses; it's about making the data the constant fuel of the enterprise, accessible to all who need it. As a result, organizations need to be able to ensure their data is viable and available. With the massive move to digital that took place recently, plus the continuing rapid evolution to reliance on digital workflows and customer interactions to stay competitive, it's time to bring data governance in line with the realities of today's intensifying data scene. A majority of enterprises in a TDWI survey found that 66% of executives said their data governance programs were not ready for the challenges of the 2020s. Issues encountered include rogue datasets (72%), managing self-service data practices (56%), ensuring quality in data and metadata (53%), convincing employees to adhere to governance policies (46%), keeping the data governance bureaucracy lean and agile (45%), and creating governance policies that are clear and usable (43%). Solutions found to be popular in addressing today's data governance issues include software tools for automating processes and procedures (72%), data cataloging (71%), data lineage (68%), metadata (67%), master data (64%), and data quality (62%), this also according to the TDWI survey. The following are ways to develop and support modern data governance approaches to align data to business requirements: Make data governance a business priority. Digital data governance should be a part of all corporate planning and decision making. Too often, it has been managed as an afterthought or as a one-off initiative. There should be collaboration and communication between all parts of the enterprise, as the data coming in from many sources is likely being maintained and validated by many teams from different parts of the organization. Ideally, the CEO and other executive leaders should be promoting data governance and data analytics initiatives. Take the lead with data governance efforts. Digital data governance requires 20 AUGUST/SEPTEMBER 2021 | DBTA Best Practices Series Enhancing DATA INTEGRATION and Governance for the MODERN ENTERPRISE

Articles in this issue

view archives of Ebooks - Data Integration and Governance for the Modern Enterprise 2021