The Basics of Enterprise Data Management

Our digital world is growing at an alarming rate. It is estimated that, by 2020, there will be 44 trillion gigabytes of data¹ created and copied annually.  However, data remains one of the most underutilised assets of any organisation. Enterprise data management is supposed to fix this paradox. Here’s what you need to know about enterprise data and how to manage it. 

Read more: Rise of Chief Data Officer (CDO) to solve the data issues 

The various types of enterprise data 

Today’s businesses, regardless of size, have to face a wide array of challenges, among which data management strikes as “the most stubborn headache” that keeps growing and never goes away. 

Data generated and used by enterprises daily is typically categorised into three types: 

1.Transactional  

This data supports the ongoing operations of the business, for example time, place, price, discount, payment methods. Transactional data is typically stored and updated within enterprise systems to describe data and to automate key processes of sales, customer service, order management, purchasing, and many more.  

2. Analytical  

These are the numerical values, metrics, and measurements that provide business intelligence and support the decision–making process. Analytical data is stored in Online Analytical Processing (OLAP) repositories, such as data warehouses and data lakes. 

3. Master  

Master data describes the core objects in business operations, transactions, and analytics such as customers, suppliers, employees, inventories, and products. Master data is usually stored in different systems and shared by multiple users or groups across the organisation. 

The enormous growth of data amidst the technological boom requires enterprises to put in 200% of effort to centralise, organise, control, and make them accessible to anyone who needs data. This happens to be the ultimate goal of enterprise data management. 

Read more: OLAP technology – Handling Big Data in the Hospitality industry 

Challenges of managing enterprise data 

The sheer volume of enterprise data today, sadly, are still handled manually, such as through conversations, spreadsheets, and emails. As information keeps generating, it is impossible for organisations to make timely decisions by going through each piece of data. 

What’s worth noting is that many enterprises do not acknowledge this is a serious issue. Few organisations do realise the increasing problem, unfortunately, lack processes and systems to unify disparate databases as well as an adequate strategy. 

Read more: Turning data into smart data 

In addition, the lack of knowledge, skills, resources, and even staffing often result in improper enterprise data management. 

On the bright side, organisations have shifted to a more data-centric culture and start implementing methods to manage their data centrally. 

What is enterprise data management (EDM)? 

Enterprise data management (EDM) refers to the process of defining, governing, securing, and maintaining every piece of data generated within an organisation. If properly applied, EDM will help create a single version of the truth to all employees.  

To achieve a single source of truth, a standard enterprise data management solution needs the following components: 

1. Data governance  

Data governance encompasses policies, guidelines, and processes established by the organisation to maintain the integrity, quality, and security of the data. Data governance must be enforced across all departments. These policies will state how, when, what, and by whom the data should be enforced. 

2. Data security  

This component includes the measures and strategies that organisations put in place to protect their valuable data assets at all points throughout the entire data lifecycle, including when data is at rest and in transit. Security measures must be established and closely monitored to not only maintain the integrity but also prevent thieveries, leakages as well as corruptions. 

Read more: Beyond Infor SunSystems 6.3 – Cloud security, AI and more 

3. Data integration  

This is the process of gathering and unifying all sorts of data of varying formats from multiple sources and repositories (in the cloud, on-premise, hard drive disk, etc.) for reports, analysis, or for later use. This is a particularly challenging aspect as the data flows through the organisations tend to be fragmented.  

A good data integration process centralises data and makes it accessible to everyone to form a comprehensive view of the entire business. 

4. Master data management 

Master data is the most useful piece of intelligence that any business owns. As it is used in multiple applications, one small error can lead to a chain reaction to every other system within the same ecosystem.  

Effective master data management helps the organisation to eliminate silos, avoid data entry errors caused by manual inputs as well as ensure the validity and timeliness of data. 

Read more: How AWS manages and maintains their massive data centres 

4. Metadata management 

Metadata is “data about other data” stored in formal storage. Examples of metadata can be report definitions, column descriptions, log files, etc. In short, metadata gives context to the data’s content. 

Without metadata, data becomes hard to comprehend, unreliable, and sometimes, useless. Metadata management ensures the creation, storage, integration, and control of these metadata are according to the predefined rules across the organisation. 

5. Data quality management 

Just like the name implies, quality management ensures that organisations acquire the highest quality of data possible. The process begins the moment information is obtained and throughout the distribution cycle. 

High quality data is crucial to having consistent and accurate analysis. Data quality management is a prerequisite to building efficient business dashboard which enables users to have a better overview of the organisation’s performance. 

Modern EDM solutions 

Infor SunSystems is a comprehensive financial accounting solution that seamlessly connects with organisation systems to provide a centralised, real-time view of the entire financial situaton. 

Infor SunSystems’ Enterprise Data Management module (EDM) allows you to synchronise key static data to business units across different SunSystems installations connected via ION. You just need to enter information about customers, suppliers, items, currency rates, etc. once and they will be propagated automatically to other business units. 

As Infor SunSystems stores data in one single, optimised repository, it is easier to look up relevant information whenever you need to. Furthermore, data also remains consistent across the organisation. 

Infor SunSystems’ Enterprise Data Management module promotes a more efficient approach to corporate data management and allows you to generate intercompany reports, close books, make informed financial decisions faster. 

To learn more about Infor SunSystems Enterprise Data Management, how this module can help your organisation to streamline both your data and your business processes, request a demo today!

References:  

1. IDC, “The digital universe of opportunities: Rich data and the increasing value of the Internet of Things”, IDC, Apr 2014, https://www.emc.com/leadership/digital-universe/2014iview/executive-summary.htm