Creating a successful big data strategy

Big data can benefit every industry across the globe as it provides insights into consumers’ minds and their buying habits. But mere data cannot help you as it requires proper planning and decision making. Thus, a successful big data strategy is required to reap the maximum benefits.

Every successful implementation requires a strong strategy and a detailed plan. The same applies for big data deployments as well. Like other projects, a big data strategy, too, needs management intent, alignment with business goals and a dedicated project management team. But, there’s more, especially from a technical standpoint. So, what constitutes a successful big data strategy?

4 steps for creating a successful Big Data strategy

1.  Deployment of data virtualization for successful big data strategy

Data virtualization provides access to both structured and unstructured data. It links both the big data sources and databases and provides actionable insights in real time. It helps the system become more agile as it provides results in real-time. Additionally, it also provides data security, which is of utmost importance in any organization.

2.  Implementing blockchain for a successful big data strategy

Blockchain is all about decentralizing authority models by excluding centralized control. It gives more importance to sharing data within a company across the globe. With blockchain, we can create redundancies to systems, including big data databases. While blockchain has huge merits associated with its implementation, there are some questions your strategy must answer:

• Suppose you work in a multinational company which has many branches all over the world. If every branch has several copies of the same data, how will you determine which is the most up-to-date copy?
• Will every branch will have its own system administrator who operates independently?

3.  Importance of machine learning for a successful big data strategy

Machine learning is an essential tool as it not only explores new data but also segments it accordingly. It can take various datasets into consideration to help make profit-reaping decisions for a company. For example, in a hospital, machine learning algorithms can be used to collect various critical data points about a patient such as her medical history, the medicines used by her on daily basis, her family medical background etc. that can direct the hospital to buy the most necessary medicines and important surgical instruments.4.  Significance of cloud storage for a successful big data strategy

Cloud storage is used across all organizations for object storage. It is not only a cost-efficient method but also gives access to large amount of data at lightning speed. With the exponential increase in data storage, management, reliability, and interoperability will be major concerns. This makes cloud storage inevitable for being used across organizations.

For a successful big data strategy, it is necessary to understand what your goals are and to look at them from a business perspective. Also, it’s imperative to involve machine learning, cloud storage, blockchain and data virtualization to take big data into consideration as it provides various trends and associations about customers’ buying habits that can help companies invest in the right place and make profits overall.