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The Mythology of Data Governance and Data Stewardship
Author: Maneet Puri
It will sound almost a cliché if you say that companies thrive on information. If you go through the front page of any news paper, watch any weather channel, come across a press conference, or go over any annual report, you will witness how data dominates the organizations today. The importance has grown so large that companies have to scour for data of the previous years to ascertain their business efficiency. From marketing department to the operation department, organizations rely on the data of every segment to make smart predictions, store historical records, and read the consumer behavior.
The volume of data grows with the augmentation of customer information. Moreover, the amount of data captured at a particular point of time multiplies every second year. Packaged applications are the norms of the present world and external data is an indispensably important component of every organization. However, old tactics and processes have given way for new ones when it comes to managing data. While the boardrooms get abuzz with the vociferous discussions on data among the executives, companies wake up to the realities of upgrading their data management processes and systems
This quest for advanced data management has given rise to the concept of data stewardship and data governance. However, the chaos and confusion over the roles between business and Information Technology continues to take place. Customer data integration (CDI) and master data management (MDM) are two important initiatives which promise to relieve business experts from the labor of defining and maintaining customer data.
The Dilemma of Data Governance
If anything has been most misused in business, it is the phrase of data governance. IT organizations have always been trying to deploy data governance to engage the business in legitimate ownership discussions. Ironically, vendors use this phrase to convey data management practices from modeling to quality automations. Worse still, even the term has been used synonymously for knowledge management and CRM. Even the IT executives mistake data stewardship with data governance.
However, data stewardship and data governance are two different concepts. Data governance is different from data stewardship in a way that it implies a level of organizational supervision that encompasses not only business but also information and technology. Moreover, it also comprises executives who desire to be a part of or are engaged with defining their companies’ policies. While they handle the internal and external regulations in one hand, they implement the customer-focused strategies on the other. Data Governance can be best defined as the mechanisms and decision-marking structures for treating data as one asset, implementing formal policies and administering the management of corporate data.
The process of data governance itself is dependant on the executive committee which institutes the policies, sort out conflicts and questions, consider customer commitments and evaluates success. Many companies that lack the processes or skills to manage their data deploy this too early in their systems. However, unless and until there is any legitimate data management and stewardship take hold, data governance will remain just a matter of discussion.
Source: http://www.articlesbase.com/
It will sound almost a cliché if you say that companies thrive on information. If you go through the front page of any news paper, watch any weather channel, come across a press conference, or go over any annual report, you will witness how data dominates the organizations today. The importance has grown so large that companies have to scour for data of the previous years to ascertain their business efficiency. From marketing department to the operation department, organizations rely on the data of every segment to make smart predictions, store historical records, and read the consumer behavior.
The volume of data grows with the augmentation of customer information. Moreover, the amount of data captured at a particular point of time multiplies every second year. Packaged applications are the norms of the present world and external data is an indispensably important component of every organization. However, old tactics and processes have given way for new ones when it comes to managing data. While the boardrooms get abuzz with the vociferous discussions on data among the executives, companies wake up to the realities of upgrading their data management processes and systems
This quest for advanced data management has given rise to the concept of data stewardship and data governance. However, the chaos and confusion over the roles between business and Information Technology continues to take place. Customer data integration (CDI) and master data management (MDM) are two important initiatives which promise to relieve business experts from the labor of defining and maintaining customer data.
The Dilemma of Data Governance
If anything has been most misused in business, it is the phrase of data governance. IT organizations have always been trying to deploy data governance to engage the business in legitimate ownership discussions. Ironically, vendors use this phrase to convey data management practices from modeling to quality automations. Worse still, even the term has been used synonymously for knowledge management and CRM. Even the IT executives mistake data stewardship with data governance.
However, data stewardship and data governance are two different concepts. Data governance is different from data stewardship in a way that it implies a level of organizational supervision that encompasses not only business but also information and technology. Moreover, it also comprises executives who desire to be a part of or are engaged with defining their companies’ policies. While they handle the internal and external regulations in one hand, they implement the customer-focused strategies on the other. Data Governance can be best defined as the mechanisms and decision-marking structures for treating data as one asset, implementing formal policies and administering the management of corporate data.
The process of data governance itself is dependant on the executive committee which institutes the policies, sort out conflicts and questions, consider customer commitments and evaluates success. Many companies that lack the processes or skills to manage their data deploy this too early in their systems. However, unless and until there is any legitimate data management and stewardship take hold, data governance will remain just a matter of discussion.
Source: http://www.articlesbase.com/
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