Enterprise Data Management and Its Crucial Components
Data is crucial for the growth of businesses irrespective of the industries they belong to. A study by the University of Texas revealed that companies couldgain 14.4% in productivity from every employee if they boosted their data usability by just 10%. Large enterprises are only now realizing that they have been sitting on a mountain of gold without ever knowing about it. They need enterprise data management at urgently for fear of missing out on a competitive edge. According to a recentTeradata survey, data tops the list of most underutilized organizational assets as per 87% of the marketers.
What is enterprise data management, and how does it solve the problem? Let’s take a look.
Understanding Enterprise Data Management
Enterprise data management, or EDM as abbreviated, is the ability of your organization of collecting, sorting, analyzing, standardizing, and integrating data to support a variety of internal as well as external applications. It can involve processes, use of software and hardware technology and implementation of policies and regulations to use data for organization’s benefit, and to get rid of any issues that might be arising due to poor or lack of management of available data. To be precise, it involves the following:
· Having proper channels to collect data
· Having the technology that collects, classifies, sorts and stores data
· Having the people who view, analyze and take advantage of this data
· Having the policies that control the inflow, storage, usage and integration of data e.g. compliance with GDPR
· Incorporating best data management practices for the growth, progress, marketing, revenue-generation, etc. of the enterprise
The Crucial Components of Enterprise Data Management
It is an umbrella term involving the processes of securing your data, and introducing policies to guarantee data quality and integrity. It is more like a source within an organization that creates the laws to define the roles of data enforcers, the way those laws are to be enforced, and the right time to do it.
You can’t just create data policies and governance regulations because in the end, you will still be sitting on heaps of data. Data integration brings the different forms of data in one place with the purpose of making it accessible. An organization has to consolidate the data that it receives from a variety of sources and make it accessible to every department in a variety of formats e.g. charts, graphs, visualizations, reports, etc.
MDM – Master Data Management
Organizations can benefit from data when it is uniform and accurate across all departments. To do that, they need a single reference source. Implementation of MDM in an organization helps repair, transform and collect data to ensure its high-quality. With MDM in place, accuracy of data is guaranteed due to the presence of a single point of reference irrespective of the diversified nature of data sources.
Data security has many facets. It involves introducing and implementing policies, methods and technologies to guarantee the intactness of data. It also involves making data usage, storage and integration practices comply with international standards such as GDPR, PCI DSS, etc. With predators lurking and regularly testing the integrity of data security at enterprises across the world its imperative to protect client data. Compromising PII (personally identifiable information) can be a death sentence for a growing data driven company as we have seen headlines across the news providing negative press. Its better to get ahead of a data breach by putting safe guards in place early.
Steps to Implement Enterprise Data Management
Enterprise-specific Requirements Assessment
The first step is to know the exact requirements of your enterprise, the existing technology culture, data sources, compatibility/incompatibility issues, etc. A sound enterprise data management strategy can only start with a full understanding of an organization’s specific requirements.
Onboarding a Data Management Team
At this point, you need a data management team that will help implement data strategies, introduce data-related regulations and policies, guarantee data integration, and ensure its security. The modern and cost-efficient method of taking on this challenge is by taking advantage of anon-demand chief data officer.
Creating the Architecture
Once you have a chief data officer, he/she will build an IT team to create a data architecture within the organization. Their work is to identify current issues, propose new technologies, outline data management policies and help implement enterprise data management best practices within the organization while meeting the highest security standards in all the involved processes.
Refining Implemented Strategies
Once the data management strategies are in place, it is an ongoing process for the IT team to keep improving the processes, methods, technologies, and policies not only to keep the architecture up-to-date with changing technological landscapes but to ensure enterprise-grade security too.
In the end, enterprise owners and managers have to realize that having a lot of data stored in their data centers is not enough. They must take advantage of the technologies and industry professionals who can turn existing marketing, sales, advertising, etc. strategies intodata-driven strategies. That enables enterprises to have the competitive edge they are aiming for.