10 Benefits of Big Data Governance for Your Organization

Despite popular belief, there needs not be a trade off between big data governance and an organizations initiatives involving big data. Big data governance also needs not eat into an organizations revenues.

What is Big Data Governance?

As the term implies, big data governance is the management of big data. Nevertheless, what is big data?

Organizations nowadays have to deal with increasingly diverse data, increasing data velocity, and increasing data volumes. This is called big data. Keeping track of big data is important because it helps businesses and organizations make informed decisions. There are several tools in the market to manage unstructured data, an example being MongoDB, which is a NoSQL implementation.

Big data concepts revolve around data creation, retrieval, storage, and analysis. To appreciate big data, note that Boeing 737, in a single flight, generates about 240 TB of flight data. Also, note that Facebook receives 500 TB of new info every day.

When it comes to data velocity, note that ad impressions and Clickstreams capture visitor behaviour at millions of events each second, there is exchange of data between billions of devices from around the world by machine-to-machine, and sensors and infrastructure generate huge volumes of logs in real time. There is also high data velocity in the online gaming world and in the stock market world.

With respect to data variety, note that data consumed by organizations is not only about numbers, strings, and dates, but it is also geospatial data, audio, video, 3D data, data from social media, unstructured text, and log files.

10 Benefits of Big Data Governance

1. Big data gives you competitive advantage by helping you unlock secrets about website usages, customer details, and other important elements of a businesss operations.
2. Data governance is important because big data undertakings pose such risks as costs not planned for and misleading data.
3. Big data is a new phenomenon, meaning data governance is at its incipient stage and few know how exactly to go about it.Governance policies and procedures are yet to be developed.Data governance companies like Remote DBA Support offer services to help companies to keep their data houses organized.
4. There are data modelling tools to assist with data governing. The best of these tools have centralized Metadata repository. This feature allows for the effective centralization and aggregation of metadata from different data sources for easy comparison.
5. Modeling tools are able to take one data stores definitions and apply them on another data store for comparison purposes. This automated process is also important in attaching some structure to unstructured or semi-structured data.
6. Big data governance helps give credence to data. You do not want data that nobody else outside the organization or even within the organization believes. Big data modeling tools are not only important enterprise definitions, but go as far as providing a graphical representation of the data.
7. Big data calls for specialized skills and expensive infrastructure. Big data governing is important because it solves the problems by incorporating cloud architecture and self-service analytics. Big data modeling has created solutions that allows organizations to cut costs and by not having to invest in extra staff or infrastructure while taking full advantage of big data.
8. Big data modeling tools allow for advanced experimentation while maintaining accuracy. This gives an organization flexibility to explore different uses of big data. Organizations  also allow for the streamlining of lab activities. The software developers responsible for these software solutions consult with mathematical and research experts to ensure the programs can handle the most demanding of scientific environments.
9. Data governing tools employ data pipelining technology, which enables sequential processing of data. One benefit of this is that the output from one process can translate into an input for the subsequent process. These pipelines are either linear or dynamic, allowing for great flexibility in data governing.
10. Big data governing tools help with proactive data quality checks, which can save you lots of grief later on. These tools also allow for proper alignment to prevent the problem of disjointed data.

Tips on Strengthening your Big Data Governance Model

1. You should come up with a data governance strategy. You could borrow from a strategy that has been tried and tested, but it is always important that it matches your unique business needs. The strategy should involve such things as ownership of different information types, who has access to the information, and for what purpose data is used. When coming up with the strategy, consider regulatory requirements, data quality, privacy, management of information lifecycle, and security.
2. Develop a cross-functional approach to data governance, which is a requirement for compliance. Information and data systems often touch different departments in an organization and not even top management can have an accurate and complete view. There should be a holistic approach to big data by a team composed of members from different departments to check on controls, auditable proof, and documentation of compliance.
3. Data has a lifecycle. Overlooking some aspects of this lifecycle, especially the end-of-life issues, is a common mistake organizations make. Do not use a standard schedule since different data types have different retention periods. Consider archiving data to enhance performance of your applications.
4. Use technology to support your data governance endeavor. Technology will assist you determine such things as how quickly your data volumes are likely to grow and the cost of data storage.
5. Consider enlisting the services of a professional to assist you with data governance. A professional will have the training as well as the experience necessary to do proper data governance, which is particularly useful in this industry since big data is a relatively new concept and your in-house IT team is unlikely to have the relevant competencies. A professional will help you make informed choices by, as an example, helping you decide between operational and analytical big data technologies and on how to get helpful clues from big data. 

Big data governance can be implemented at the beginning of your big data implementation or while the implementation is ongoing. You can also read more at https://remotedba.com/