Information trends have always been an important part of business, however in the era of Big Data, it has moved from important to essential. Much of the conversation around Big Data has been focused on the technology necessary to collect and store information. This is an important conversation, but we should also be paying attention to why data needs to be governed and how to manage it reliably so that sound decisions can be made.
Data usage begins when the source data enters the organization. There are various entry points for data after which it is merged, cleansed, transformed, and consolidated. These data points are aggregated into a data warehouse and subsequently queried or get “data-marted” for specific analysis. Decisions throughout the organization are supported by analysis of this data, be it operational, tactical or strategic. Important decisions depend on data being complete, understandable, and of the highest quality. Here’s how you can ensure this in five steps:
1. Define Data Owners & Stewards
In the world of Data Governance; data owners, data stewards and systems owners & stewards are all important roles. Roles are defined with the establishment of key players in these capacities – Committee, Program Office, Working Groups and Stewards. Data ownership establishes accountability and responsibility quickly.
2. Establish Priority
Does your organization have data hemorrhaging in specific areas that severely affect decisions? Treat these issues first so that the foundation can operate normally and create stability in the environment. This gets you a “quick win” and establishes the value of data projects to the business.
3. Seek Sponsorship and Create Champion
An important component for the success of Data Governance is executive sponsorship. Resolution of data issues will effect many parts of your organization, things could get territorial. Data Governance will expose problems related to process, technology, or people. Data can be a powerful indicator of success and failure. To harness data’s power, you will need champions and all the executive support you can get.
4. Support with the Right MDM Tool for Measurable KPIs
The right MDM (Master data management) technology when combined with Data Governance will help you validate results. You will need to conduct an in depth assessment to determine the correct MDM. Create a master set of elements (Vendor, Products, Customers, Employee) amid data cleansing, merging, transforming and integration. This is where success criteria (KPIs) are established with data owners and stewards. KPIs must be measurable, managed and monitored, which is why working in conjunction with an appropriate MDM tool will greatly enhance success.
5. Create Accountability with Team Member
The data owners, stewards, working groups and IT systems are the mechanical components of the Data Governance organization. Each of the members of these organizations must maintain their data. They create, edit, transform, delete and archive data elements.
Bad data can have extensive repercussions within your organization. It could mean losing huge revenues through operating under the wrong assumptions and making the wrong decisions. This is what sets the stage for useful data analytics and insight. The above is simplified, but gets you familiar with the fundamentals of Data Governance & MDM.
Patrick has nearly 20 years of experience developing and leading Business Intelligence solutions and strategies. His specializations include data warehousing, data integrating, data analytics and visualizations, data governance, Master Data Management, enterprise applications, and program/project management. Patrick enjoys fishing, hiking, running, repelling and is a professional soccer referee. To learn more about Patrick check out his LinkedIn here.