Today, we are seeing a burgeoning task among organizations. This task is around adopting, integrating, and managing enterprise data that is constantly moving through their systems; needless to say, the quantum, of which is rising in leaps and bounds.
Business CXOs can leverage this data ecosystem and gain a huge competitive advantage. However, the study suggests that most business leaders do not have their data arranged and managed properly and effectively. According to the 2018 Global Data Benchmark Report, published by Experian, organizations in the United States believe that 33% of their customer data is having some of the other inaccuracies. This is disastrous because poor data quality can negatively impact everything – right from business intelligence resulting in wrong decisions to the productivity of employees (as it creates duplicity of tasks resulting in loss of time).
What is enterprise data management?
Enterprise data management is a process of managing, monitoring, and storing enterprise-wide data and most importantly, getting the entire organization on board with the process. To put it simply, while EDM is about managing data, it is also equally critical about managing people. Data management is nothing but ensuring that people in the organization have accurate and timely data as and when they require it. Furthermore, they should also ensure that the data is stored in a standardized, and secured place.
Why is enterprise data management important?
Enterprise data management is important because it delivers a highly standardized and streamlined system to organizations. Through this system, companies can search, manage, access, store and secure their data. Enterprise data management also ensures that companies can easily find and analyze the data for their internal analysis and thereby take well-informed decisions and define strategies around these decisions.
Enterprise data management use cases
Effective EDM helps organizations to transfer data to other business applications, processes, and users with relative ease. Having achieved this results in significant improvement in operational efficiency and efficacy.
Moreover, enterprise data management also delivers an internal benefit to organizations in the form of cutting down the time spent on new data regulation. Effective EDM also helps in managing and controlling any sort of changes or fluctuations in assets. This strengthens the trust in overall policy across the organization.
An EDM helps companies to:
- Store, search, use and analyze data
- Take well-informed decisions across the organization
- Prepare for the future
- Streamline processes
- Improve efficiency and efficacy of functioning of users
- Re-enforce trust
To sum up, enterprise data management ensures the storage of accurate and accessible data, but in a secure way.
Benefits of enterprise data management
Having made enterprise data management a top priority, organizations ensure that the data is stored in a secure place and is made available to users whenever they need it. By ensuring the following protocols are taken care of, enterprise data management brings about significant benefits:
- Getting access to data of high quality for performing analysis
- Making sure that the data is compliant with standard guidelines and regulations
- Consolidation of data from multiple sources for enhanced efficiency
- Ensuring a stable and consistent data architecture that can scale up with the organization
Moreover, the task of data analysis and other relevant activities can be performed more efficiently because people know exactly where to find the data they need. Furthermore, if the data is well organized and stored data can help organizations to identify any sort of discrepancies in the data and the accessibility of data among the user group. This can help data managers to define right table structures and make those easily accessible to users.
Enterprise data management best practices
As mentioned earlier in this article, enterprise data management is as much about managing people as it is about managing data. Hence, when an organization plans to start an enterprise data management initiative, they need to keep the following best practices in mind.
- Data managers must get buy-in from the executive leadership team, particularly the Chief Technical Officer (CIO) or the Chief Information Officer (CIO)
- Teams need to be appraised with the importance of data management and they should also follow guidelines to the dot
- Prioritize security and governance of data
- Data cataloging is very critical
- Constantly improve the data access to relevant teams and user groups
- Harness the capability of the latest technologies around data cataloging
There are many tools that data managers can use to start the work on data management at their end, even before it kicks off at the organization level.
Components of enterprise data management
The very first step in the process of enterprise data management is to complete the task of a data audit. The person leading the data management exercise will list out the data that was produced, used, or deleted during the course of a business process. This is known as data cataloging, and this kind of exercise is pertinent to derive the larger picture of the data. Cataloging has to ensure that every single bit of data from every source, including notes and emails is captured and stored.
Once the data is cataloged, then the stored data needs to be cleaned up and transformed into a standard format. The process of data cataloging, data cleansing, and data preparation can be a cumbersome task, however, once accomplished, the organization is one step closer to data management.
Master data management vs. enterprise data management
It has been over a decade where professionals have been talking and contemplating the differences between Master Data Management (MDM) and Enterprise Data Management (EDM). Broadly speaking, the term MDM represents pretty much the same – standardization, management, quality, and governance of any mission-critical data in any business domain and not just limited to financial markets. However, EDM, broadly speaking is the capital market term for MDM and MDM is a generic terminology.
However, there have been discussions and appearances of multiple connotations and differences between EDM, and MDM. Industries derived from these connotations in their own way. For instance, companies that trade in financial markets require information related to the securities that they are trading. However, other industry verticals such as health care or manufacturing do not require that. If we look at the journey of many financial services organizations, they started their data management journey with the security master. Thus, it becomes a logical assumption that such securities mastering projects are more linked with EDM projects.
On the other hand, the majority of industries, including the financial services vertical, have a requirement of mastering entity-level data. This includes touchpoints such as individuals, corporations, hierarchies, and much such information). For such projects, the terminology MDM can be associated with because these are generic in nature.
To summarize, enterprise data management is a very critical element for any organization. This is visible with the fact that companies are spending millions in ensuring that the right EDM framework is defined and implemented by harnessing the power of tools such as Tableau, Stitch ETL, and other similar technologies.
Enterprise Data Management is a very pertinent component of the overall GRC framework defined in the organization and we will be seeing more expansions or derivatives of this process, in years to come. Technology will also evolve making the life of executives a tad better than what it is today.