Enterprise data management (EDM) is defined as an enterprise’s ability to identify, integrate, restore, and stockpile data for internal applications and external communications. EDM exists to ensure the credibility of all the data assets of the organization. This article discusses the key elements and importance of EDM and shares some best practices for 2021.
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What Is Enterprise Data Management (EDM)?
Enterprise data management (EDM) is an enterprise’s ability to identify, integrate, restore, and stockpile data for internal applications and external communications. EDM exists to ensure the credibility of all the data assets of the organization. With EDM, companies can engage in informed decision-making and analytical planning through useful, accurate data.
Today, many leading organizations rely on EDM for inventory and governing business data as well as the people who manage this data. EDM solutions ensure accurate and timely access to information and enable the standardized, safe, and controlled storage of the said information. Under EDM, a wide variety of organizational assets are managed, including financial data, inventory, mobile data, social media, IoT, photos, videos, and other graphics. EDM can create catalogs for internal as well as external assets.
In 2021, where physical interaction between people is at an all-time low globally, data is the lifeblood that drives the whole world. This is why corporations require a comprehensive enterprise data management strategy to harness the complete value of their information. However, the reality is different.Â
Many organizations are having trouble in adopting, integrating, and managing the business data moving through their systems. Experian’s Global Data Benchmark Report 2018 suggests that organizations in the U.S. believe up to one-third of their customer and prospect data suffers from some form of inaccuracy. This is bad for obvious reasons. Sub-optimal data quality pulls down everything that it touches, from productivity levels being affected to analytics and business intelligence, throwing up wrong conclusions.
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Need for robust EDM strategy
To address this data inaccuracy, a robust EDM strategy is necessary. It is vital for data flow within an organization to undergo end-to-end management, from entry and storage to modification, analytics, and reporting. The EDM strategy of an organization should be designed based on its specific requirements.
Answers to these four questions can help guide the formation of any EDM strategy:
1. How should data exploration be facilitated?Â
Data exploration processes typically involve the use of data visualization, statistical programming, or business intelligence tools to derive value from data.
2. How is data collected for analysis?
Any business that operates online generates large volumes of data. When it comes to analytics, selecting the most relevant subset for business intelligence can be difficult. EDM can help ensure the collection of rich raw data through ETL and proper storage in a data warehouse.
3. How are disparate data sources consolidated?
The technology used by organizations to extract data from all systems and prepare it for analysis is known as a data pipeline. After considering the business needs carefully, a data pipeline should be chosen accordingly.
4. Which technology should be used to store and analyze data?
The most optimum data warehouse solution must be considered. Robust EDM policies, tools, and procedures help businesses keep their data accurate, secure, high-quality, and available. Distinct competitive advantages can also be seen in the form of timely and accurate business intelligence and analytics, a boost in employee productivity due to reduced rework, and the rise of new business opportunities and revenue streams due to reliable, useful insights.
Forms of enterprise data
Enterprise data includes all the digital information that flows through a company’s systems. The primary forms of enterprise data include structured data (spreadsheets and databases) and unstructured data (images, videos, and other graphics).
Examples of enterprise data include:
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- Operational data such as customer orders, transaction records, accounting and billing systems, or internal HR statistics.
- Network logs and alerts used by cybersecurity or development teams to manage IT infrastructure.
- Strategic data gathered from sales reporting, customer relationship management (CRM) systems, external sources of market data, or trend and opportunity analyses.
- Application-specific data such as GPS data for transportation and logistics, data from IoT sensors, information about the weather, and social media content.
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Key Elements of EDM
The true value of advanced, cohesive components of EDM lies in encouraging data security and awareness as well as a holistic focus on the meaning and utility of data, rather than merely volume and velocity.
Key Elements of Enterprise Data Management
Here are a few key practices, processes, and activities of EDM:
ETL/ELT
Extract, transform, load (ETL for short) defines processes used by a data pipeline to source and recreate data from a system and replicate it into a target system such as a data warehouse.Â
True to its name, the process is pretty straightforward: ETL extracts information from a source that is not optimized for analytics and then shifts it to a centralized, analytics-optimized host. ETL plays a critical role in the EDM ecosystem by simplifying data transmission from the origin to its destination.
Data quality management
Data quality management, commonly shortened to DQM, is an amalgamation of the perfect technologies, processes, and people working together to enhance important data quality measures within an organization.Â
The main goals of DQM are to boost data quality, ensure the availability of high-quality data, and achieve the best possible business outcomes using the aforementioned data. Through DQM, an organization can focus on discovering underlying problems in its data and addressing them through processes such as data cleansing, integrity checks, enrichment, and quality assurance.
Master data management
Master data management, often known as MDM, is the management, organization, centralization, localization, categorization, synchronization, and enrichment of master data based on business rules of the marketing, sales, and operational strategies of an organization.Â
MDM processes help ensure that a company uses only one version of data that is correct and useful—also known as a ‘golden record’. Using MDM, employees can reconcile integrated and varied data and ensure consistency in downstream analytics and applications. MDM removes duplicates, applies modeling rules, and aggregates reporting records.
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Data integration
As the name suggests, data integration processes are leveraged to integrate data from multiple sources into a single, amalgamated view. Ingestion is the first step of the integration process—this step includes ‘sub-steps such as cleansing, transformation, and ETL mapping. Ultimately, data integration allows analytics solutions to generate business intelligence that is both actionable and effective.Â
By creating a unified repository, data integration makes data actionable, valuable, and available to anyone who needs to access it. Other advantages of data integration include enhanced system collaboration and unification, savings in time, minimization of rework and errors, and assurance of valuable data for decision making.
Data stewardship
Data stewardship includes the management and supervision of organizational data assets to help business users easily access high-quality and consistent information. Stewardship activities focus on operationalization, execution, and management of the data lifecycle, from curation to retirement.Â
By ensuring adequate data stewardship, organizations can avail data that is consistent with in-house data governance plans, linked with all relevant databases, and monitored in terms of compliance, data quality, and security. Defining data models, model maintenance, data documentation, data cleansing, and defining policies and rules are key components of data stewardship.
Data warehouses
Data warehouses store large collections of business information that can be used to help a company in its decision-making processes. These repositories are used to securely store contemporary and historical data collected from disparate sources.Â
A data warehouse can be either on-premise or cloud-based. It is a critical element of data analytics architecture and serves as a medium for analytics, decision support, data mining, and business intelligence. Interestingly, ‘data warehouses‘ have existed for over 30 years and were developed to enable data to go from helping run operations to driving decision support and business intelligence systems!
Data governance
Finally, we come to data governance — a set of processes that form the basis for any successful MDM program. Data governance programs include stakeholders from across the enterprise and ensure that the right data responsibilities are assigned to the right people.Â
These processes include creating a structure for external and internal accountability and streamlining the organizational flow of data. With proper data governance, an enterprise can be assured of optimum protection of user privacy, efficient adherence to rules and regulations, and ethical execution of responsibility at all levels.
Also Read: What Is Data Security? Definition, Planning, Policy, and Best Practices
Importance of EDM
Simply put, enterprise data management is important as it creates a standardized and streamlined system for enterprises to locate, access, control, store, and secure their data. With EDM, companies can make the most informed and statistically best decisions and engage in day-to-day operations from a data-driven perspective.
Using effective EDM, organizations can transfer data to varying processes, applications, and partners with confidence, success, and ease to streamline processes and enhance operational effectiveness and efficiency. Another crucial benefit of EDM is the reduction in time and effort utilized by organizations to regulate new data. With effective EDM, enterprises can organize and manage continuous fluctuations and changes in assets, strengthening overall trust in their content and policies.
The following points further exhibit the importance of EDM within an organization:
Higher productivity levels
When it comes to productivity, easily accessible data makes a huge difference. The larger the enterprise, the more difficult it is for employees to get the data they need when required—sending emails, raising tickets, and taking necessary authorizations all affect productivity. Just think about how much more productive and organized your entire organization will become if everybody can access data as soon as they need it!
EDM systems allow employees to access the information they need with ease, which means less time is spent ‘looking’ for data and more time is spent ‘working’ with it! This directly leads to enhanced efficiency. EDM also boosts productivity differently: ease of access means an increased ability of employees to comprehend and share data, which, in turn, means human error is significantly reduced.
Smoother workflows
Regardless of a ‘reduced workforce’ due to COVID-19, the modern consumer does not like to wait. If an organization is taking too long to respond appropriately to customers’ needs, such customers will likely take their money elsewhere. The seamless functioning of organizational systems is critical for any business to operate properly, and investing in EDM systems brings enterprises a step closer to achieving this goal. EDM could be the difference between a happy, productive organization and one that has frustrating workflows.
In 2021, where remote work is the norm, EDM can help any workforce stay competitive and successfully achieve its company’s goals. EDM allows workflows to run smoothly and employees to fulfill client expectations promptly. By investing in an efficient EDM system, enterprises can keep their consumers satisfied.
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Decreased security risks
Since the COVID-19 pandemic began, the internet has become the primary way for organizations to do business. Numerous enterprises are keeping their entire operations limited to an online environment.Â
With this, of course, comes the risk of compromise: there are several illicit ways the wrong person can access digitally stored business information. EDM solutions come with ‘maximum security’ features that protect all enterprise data from nefarious elements. Cutting-edge EDM protects sensitive data and keeps threat levels at a minimum.
Increased affordability
Incorrect client information can be a costly affair, as can involuntary data duplication. Efficient EDM systems are cost-efficient because they help organizations deal with data management problems, such as information duplication and incorrect data, which can be caused due to human error and merger and acquisition processes.
Minimal risk of data loss
Data loss is a problem that needs to be addressed at the organizational level, and EDM helps prevent the loss of key enterprise data by ensuring timely and complete backup. In exigent situations, EDM systems allow organizations to retrieve critical information without any hassle.
Enhanced decision making
The COVID-19 pandemic and ensuing remote working have led to impaired decision making, as communications fall apart due to various reasons, such as digital ineptitude or lack of awareness around correct work communication etiquette among employees.Â
EDM keeps the entire company up and running by ensuring that all information is where it needs to be—accurate, secure, and available. When all departments are fully functional, decision-making processes are suddenly enhanced, and the decisions that are made are suddenly of a higher quality threshold. Decision-making plays a critical part in organizational success, and EDM can help businesses evolve even as they continue to work in a remote environment.
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Top 10 Best Practices for EDM in 2021
EDM processes involve managing data as well as the people who access it. In 2021, remote work continues to dominate the business scene, and data management has become more critical than ever. As enterprises move towards EDM to manage their disparate data sources, both internal and external, these simple best practices can help:
 EDM Best Practices 2021
1. Begin with an EDM audit
The goals of this audit should be simple: to see whether EDM leads to enhanced revenue, increased operational efficiency, and higher-quality customer experiences for the organization. As the audit progresses, auditors should list the things that the company is doing right and wrong in terms of enterprise data management.Â
By conducting a thorough inventory of the data that is already present within the organization, its sources, processes, governance, and storage, auditors can gain a comprehensive view of the current situation within the organization, be aware of improvement areas, and implement them as and when necessary.
2. Set clear objectives
Once the audit is complete, the management team can use the findings to outline metrics to track progress and ensure improvement. A strategic plan for improving the data situation within an organization can help answer the following questions: What aspects should be tackled first? What timelines work for EDM implementation? What is the perfect budget for this exercise? Remember, objectives need to be realistic, and success should be defined clearly at every stage.
3. Ensure data quality
EDM works best if the quality of data input is high. Simply put, data quality underpins everything that comes after it, ultimately affecting customer satisfaction and profitability. As such, investing in high-quality data helps enhance RoI, from EDM implementation through better, more significant insights.Â
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4. Identify data management leaders
Any effort requires strong leaders to be successful, and EDM is no exception to this rule. To ensure successful enterprise data management, contributions would be required from the leaders of all business units within an organization. Enterprise leaders with a background in IT, business intelligence, and analytics can aid in creating and implementing an EDM strategy that is robust and effective.
5. Implement strict data governance processes
Data governance helps ensure high-quality and consistent EDM operations. Start by removing any doubts around conflicting data sources, which will enable employees to achieve the ‘golden’ version of every piece of data. Next, implement strict standards to achieve robust data integrity. Finally, create a culture of data accountability within the enterprise, and assign responsibilities appropriately to ensure accurate data sets.
6. Obtain executive backing
The most successful business projects have executive support at all levels. For EDM, this can be achieved by showing executives a clear business case to justify the project’s investment. Formulate a comprehensive list of advantages of EDM and how to track them against set business goals. By bringing executives aboard for EDM, long-term success is all but guaranteed.
7. Choose the right EDM technology
EDM relies on technology as much as it does on the people running that technology. Find the right EDM technologies and tools, train employees to use them efficiently (more on this in the next point), and implement processes around them to promote correct usage across the enterprise.
8. Train and educate employees
Even the strongest EDM initiative will be unsuccessful if most employees are not in its favor, any initial excitement notwithstanding. EDM is a proven solution for transforming business operations over the long run, but maintaining employee support for this initiative through the initial challenges is critical.
This commitment can be achieved by disseminating adequate training and education to employees at all levels about the benefits of EDM for them and the organization as a whole. The ‘hows’, ‘whys’, and ‘whens’, all need to be answered in detail during these training and education sessions.
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9. Consider hiring an EDM specialist
A specialist, especially an experienced EDM officer who is given a high rank within the organizational structure, is best suited to elucidate the significant risks that an organization faces when managing customer data, such as damage due to poor data quality or data privacy breaches, as well as to prepare the organization as a whole to deal with these risks to prevent substantial losses due to rework damage, brand damage, regulatory fines, and other causes.
10. Finally, keep going!
When it comes to any major process within an organization, open and transparent two-way communication is integral. Naturally, the same holds true for EDM. Far from being a one-time process, EDM is an ongoing effort that needs regular improvements and adjustments to ensure organizational success in the long run.
Also Read: Top 10 Data Governance Tools for 2021
Takeaway
Even though several COVID-19 vaccines are gaining prominence in 2021, remote working does not seem to be going anywhere anytime soon. As every communication point becomes either an email, a message over the company’s preferred collaboration app, a virtual meeting, or a phone call, employees are often dealing with too much data to track. Things are pretty much the same on the other side of the coin: with businesses having shifted all operations online, customer data is flowing in at an unprecedented rate. These ultimately lead to the same outcome: lots of data flowing into organizational systems.
To ensure seamless management of all this data, EDM is critical. Apart from defining and managing strategies for technologies, people, and processes, EDM also ensures that an organization’s key information is managed and protected across the spectrum. With EDM, data is governed in a way that ensures accuracy, completeness, trust, and understanding. EDM solutions help govern the enterprise to reduce risk and ensure both internal and external compliance.Â
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