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Data security breaches and regulatory data storage requirements are forcing businesses to place data governance at a much higher priority today. Companies are quickly implementing policies to store data, secure it, and make it available while laying down access plans that define who can view the data, use, and share.
Key Attributes of Data Governance
Data governance policies are about encompassing the entire data lifecycle, starting from data collection to curation. Within that data lifecycle, the policies should address the following issues:
Data Sourcing: The lifecycle of data starts with data sourcing, or the collection of data. The sources determine the foundation of data governance. Where is the data coming from? What is the incoming data stream? Is it coming from existing customers, a targeted market, or social media? Is there an external vendor collecting and analyzing the data? Data governance must address these questions while formulating the data collecting policies.
Validating the Data: Data collected from various sources can get a bit problematic if you are not sure about whether the data is sound. In all cases, data governance should have policies to validate the legitimacy of data, irrespective of its source.
Storage: Data governance policies must address strategies for storage, depending on the size of data sets. Data should be stored in a hierarchical system to make it available based on the frequency of its use.
Usage/Sharing/Analysis: How data is being used, shared, and analyzed are crucial components of the data governance policy. Shared data must be carefully defined and protected against security breaches and attacks. Compliance with respective regulations regarding the use of data is another key part of the data governance policy.
Curation / Metadata: The data lifecycle is incomplete without curation. Curation essentially involves the application of metadata to a data set so that it can be identified for retrieval. Metadata can include the source of data, date of collection, semantic classification, access level, and other attributes as specified. Data governance policies should be able to define parameters and establish metadata vocabulary for the shelf-life of data.
Steps for Successful Data Governance
1. Create Data Governance Organization
The Data Governance Institute (DGI) recommends the formation of a data governance board, which can meet the multiple needs and demands of external users, inside users, and even statutory demands. It is important to include business stakeholders and security experts in the data governance board with representation from all kinds of data ownership. It is crucial to articulate the role of the data governance board with respect to the policies that are to be undertaken.
The data governance board is a continuous entity, which should be able to accommodate future governance policies as business areas expand over the time. Moreover, the data policy, with the emergence of new technologies, should also evolve to keep pace with data analysis methods, disruptions, security developments, and data management tools.
2. Develop a Framework
The framework should ensure the accommodation of unified data that complies with the collection, storage, retrieval, and security requirements. Organizations, to enable this framework, will have to strategize an end-to-end data policy. All necessary components need to fit together so that the retrieval requirements can be performed in a high-security environment. Validating the data before putting it to use will be the central role of this framework along with adhering to the regulatory mandates.
3. Pilot Data Strategy
Typically, before implementing bigger steps, a pilot project should be rolled out covering a small section of the organization. This helps in identifying the flaws in the overall strategy, the infrastructure, and the framework governing the policies.
4. Understand the Goals of a Successful Data Strategy
Strategize criteria for success, and set benchmarks so that progress and success can be measured along the way. Defining data management goals helps in identifying whether the data governance strategy is moving in the right direction and yielding results as desired.
5. Rethink Your Approach Towards Storage
Apply a new mindset to understand how data can be stored in a way that the data infrastructure is fit for purpose. For this, you need to explore different storage platforms that can support the variety of data needs your organization has and the associate costs. Cloud solutions might work for some of your data, while on-prem storage makes sense for other data sets.
Both large and small businesses face some type of data challenges. The bigger organizations, with big data sets, need to build a formal data management strategy while the smaller ones, with lesser data, can do well enough with an informal data governance policy.
F3 Technology Partners addresses the storage needs of small to larger organizations with solutions for any storage-related issue. F3 has solid partnership with the industry leading IT manufacturers. Whether it is sizing a specific storage project, determining cloud-based storage solutions or troubleshooting a performance issue, F3 is committed to helping our customers protect their most valuable asset; data.
As your technology partner, we can help you make the best storage decisions based on the current – and future — requirements of your business and enable you to leverage the storage environment that best fit for your business needs as well as budget.