Introduction
Typically, businesses begin their road to big data by experimenting to determine whether big data can help define and influence company strategy. However, once it is evident that big data will play a strategic role in the information management environment, the organization must ensure that the proper structure is in place to support and safeguard it.

Let’s learn about how to put the right organizational structure.
Putting Right Organizational Structure🎯
Before establishing policies, you first have to know what you are dealing with. For example, are you intending to use transactional systems, social media data, or machine-generated data? As part of your data analytics strategy, do you plan to incorporate data from these many sources? If you plan to do more than a single experiment, you'll need to change your governance strategy to ensure that you're ready to handle a new type of data securely.
Preparing for Stewardship and Management of Risk👨💻
Whatever information management system you choose, you must ensure that the appropriate level of control is in place. This is simply a great practice in general, and it is unaffected by the addition of big data. However, including massive data sources may necessitate a different approach to data stewardship. Because social media data has a different origin and structure than traditional relational data, you might need to have a different person monitor it. This new data steward role must be carefully defined so that the person chosen may collaborate across business divisions that find this type of data the most useful in their analysis.
For example, the data steward must know or have access to the right personnel who see the company's data retention policy and the requirements for hiding out personal data regardless of where it comes from.
Setting The Right Governance and Quality Policies
How a company handles big data is a continuous process, not a one-time effort. If consistent standards and procedures are not followed consistently, the risk to the firm might be significant. Data quality should be treated from a governance perspective as well.
When it comes to policy, consider the following important components that must be written to protect your organization:-
👉 Determine the best practices that your peers have used to establish consistent policies so that everyone is on the same page.
👉 Examine your policies in light of your company's and industry's governance standards. If you discover any flaws in your policies, make the necessary changes.
👉 Do you have a policy that dictates how long you must keep information? Do these policies apply to information you gather from third parties, such as consumer discussion forums and social media sites?
👉 What value do you place on the data sources you're bringing into the company? Do you have quality control procedures to ensure that data collection is only utilized for decision-making once it has been confirmed to be clean and adequately documented? It's tempting to get caught up in the excitement of using big data to do previously impossible analyses. Your business, however, will be jeopardized if the study leads to wrong conclusions. Extraneous data might influence sensor data, causing an organization to conclude incorrectly.