Data Management and Governance Services

Simple and effective approaches

De: Tejasvi Addagada

Narrado por: Virtual Voice

The book provides frameworks for business, operational, and technology leaders that are simple and effective in managing data. Many data offices have challenges in actively managing data and deriving consistent value from the data science, Bigdata and reporting programs. While few challenges can be cultural, some can be related to the way the people are enabled or toolsets are pulled for self-service. The handbook provides proven approaches to either start managing data with simple frameworks or to mature the existing practices as standard and nimble services. Choosing a right operating rythm that wisely blends people, process and toolsets, is quite important for data to be governed and to impact the corporate governance levers. With the right enablers - Trust can be built in internally with the organization as well as within shareholders who would consider the organization as a 'data-trust'. Most industries actively manage and govern their data primarily to be compliant with regulations or to derive an outcome from data in their landscape. While it is important to set up a formalized data office, it is also crucial to proceed with sustainable operations to realize continuous business benefits. Also, data governance is a pervasive enabler that supports a firm’s corporate governance principles in order to build trust in regulators, customers, and investors. The book explores the contextual challenges, in-depth, in Fortune 500 companies, using 5 Case-studies. The narrative takes you deeper into attaining maturity within data quality and metadata using a service-based-model that assists the data offices in overcoming challenges including data complexity, sub-optimal data quality, and in-consistent data value chains. Further, the author specifically details: 1. How can an organization overcome cultural and communication challenges in data offices today 2. Formalizing a data strategy using a maturity assessment of capabilities 3. Build maturity by setting up data quality and metadata management as standard services 4. Formalize governance as a function through an operating model, based on the firm's enabling culture 5. Define a benefits-realization model to assess and monitor the value of managing and governing data