Enterprise data management (edm) is an important process in big data for understanding and controlling the economics of data in your enterprise or organization, for organizations failing to provide good data governance, data has the potential to become a major liability, also, for example with the rapid adoption of Apache Spark at your enterprise level, now more than ever it is imperative to secure data access through Spark, and ensure proper governance and compliance.
Enterprise Data Governance serves a critical function in business to support regulatory compliance, and it is also crucial to ensuring a common understanding of organizational data assets across your enterprise, application proliferation has created identity fragmentation as user identities are inconsistently managed across applications in your enterprise, increasing risk, unfortunately, one of the many challenges that Data Governance practitioners face is the inability to make the mandate for data governance stick in organizations.
Implement the security needed to create a consolidated and integrated enterprise data warehouse, and to improve data quality, understanding and visualization, provisioning and deprovisioning set up access to organizational Data as authorized by the Data Steward, additionally, another big challenge that Big Data has imposed on Data Governance is the required level of Data Quality to meet your enterprise Data Management goals.
As your enterprise admin, you have access to additional security capabilities that enable you to set account-wide security settings for your managed users, strong data governance is needed to manage the availability, usability, integrity, and security of the data used throughout your enterprise so that data are of sufficient quality to meet business needs, especially, although maturity levels will vary by organization, data governance is generally achieved through a combination of people and process, with technology used to simplify and automate aspects of the process.
Information governance advisory services leverage your experts and staffing services to help you establish a program that can reduce the costs and complexity of managing your information throughout the lifecycle, without a data governance operating model, coordinating Enterprise Data Governance requirements and ensuring compliance is a complicated endeavor, in addition, IoT data governance covers full lifecycle of the data, starting from data generation in the devices, sending the data over the network to Cloud-based IoT platforms, storing the data, and finally analyzing and reporting on the data.
The complementary nature of data governance and information governance is especially critical for organizations that are hoping to engage in big data analytics, since each individual data set must be clean, accurate, standardized, and comprehensive before it can be combined with additional data sources to produce actionable insights, meet eDiscovery requests, data retention policies and support global security, privacy and compliance standards, in the first place, instead of seeing GDPR and data legislation as a bind, your organization can use data governance and security as a competitive advantage.
Scale across lines-of-business, enable proper governance of your data assets, ensure your data is locked-down and secure, and deliver a continuous flow of data to your business teams, most organizations have multiple Siloed sources of data, vendor driven portals which have market intelligence and competitive insights, and internal systems have internal data, in light of this, the objective is to control data at the data level and to ensure integrity through appropriate systems and processes.
Ensure development projects meet business requirements and goals, fulfill end-user requirements, and identify and resolve systems issues, data governance is distinguished from other types of data management in that it provides a higher level of handling and management of data to ensure security and accuracy, similarly, building strong digital foundations that focus on data availability will have to be vital to the future of every organization.