Big Data is the process of mining and processing of petabytes’ worth of information to gain valuable insights into how customers behave, supply chain efficiency and many other aspects of business performance which requires big data analytics.Industry-based research has shown that early adopters of Big Data analytics have gained a commendable lead over those who have not yet tapped into this.Big data management has since been recognized as an important, competitive tool, the use of which requires a company to make three kinds of table stakes.The first stake includes the data itself: large quantities of information in a format that allows for easy access and analysis. A majority of large companies are already in possession of this.The second stake involves advanced analytical tools, such as proprietary and open-source tools and platforms that are widely available nowadays.The third and most challenging stake includes expertise. Advanced big data analytics requires professionals who possess state-of-the-art skills in everything, ranging from data science to privacy laws all around the world, apart from developing an understanding of the said business and the relevant sources of value.However, these stakes are just a part of the bigger picture since Big Data is more of a business program that requires technical savvy rather than being another technical initiative.Analytics leaders have stipulated that in order to succeed with Big Data, it needs to be embedded deeply into the organization’s infrastructure. Embedding this into the very structure of the organization is the only way to make certain that information are shared across business units and functions and used judiciously.A good big data solutions program requires ambition on the part of the organization, a strong horizontal analytics capability and an organizational home for the big data analytics.Leading companies begin the big-data embedding process by spelling out their ambition with regards to using Big Data as a new way of doing business. Incorporation of advanced analytics and insights as key elements of all important decisions is one of the main steps towards realizing this ambition.There are four areas where analytics can be relevant:improving existing products and services, improving internal processes, building new product or service offerings, Transforming business models.These objectives may often overlap.To look at an example, Humana, an insurance provider, uses Big Data to transform its business. Using its claims data, the company can determine who is likely to end up in a hospital for preventable reasons and then intervene at an earlier stage. Humana and other health insurance companiesalso mine data to help improve patient outcomes and reward healthy behaviors.Horizontal analytics capabilityOnce an ambition has been defined, Big Data leaders work on developing a horizontal analytics capability to overcome internal resistance, and create the infrastructure to use data throughout the organization.For example, a global consumer electronics company selected high-impact analytics projects for extra support that creates positive business outcomes and an increased demand for Big Data solutions. The company further gave increased incentives to senior executives to tap Big Data capabilities and provide for Big Data services in USA.Organizational homeWith regard to the horizontal analytics capabilities, big Data leaders then create an organizational home for the advanced analytics capability that is often known as a Center of Excellence (CoE) that is overseen by a chief analytics officer.Creating an organizational home requires several key design decisions like setting a strategy for Big Data deployment, assigning collection and ownership of data across business functions, planning the generation of insights and prioritizing opportunities and allocation of data scientists’ time, hosting and maintaining the technological infrastructure, setting privacy policies and access rights, and determining the accountability for compliance with local laws and data security.To start with the big data solutions, one must benchmark the industry and determine the company’s current position in Big Data analytics and capabilities as compared to the most immediate competition. Following this, other decisions can be fathomed as to how big data can help your organization to grow fast.