Big Data is about answering business questions. With in-memory data structures, file based storage systems, and massively parallel processing, today we are able to leverage advantages from data. To dig information from that data, any business need to create a functional model which solves their business problems and get the right technology for analytics. Here is where we need data maturity. Maturity is required as accepting predictions and more sophisticated analytics without a trust is not possible to attain. Officially, Big Data Maturity Models are the artifacts to measure Big Data maturity.
These Big Data Maturity Models help the companies to create structure around their Big Data strategy. In other words, it can be described as a methodology to measure a company’s big data capability or the required future effort for the next stage.
From the above explanation, it can be guessed that the Big Data Maturity Models can be very useful. Most of the analyst firms have created some sort of maturity model. A maturity model can be a benchmark. They can provide a roadmap. Different maturity models measure different matters. The goals of Big Data Maturity Models provide a capability assessment tool to focus on big data in the organizational areas, guide development milestones and avoid pitfalls. Big data maturity models can divided into three broad categories :
- Prescriptive models
Each of the above categories have own maturity levels, which is of theoretical interest. The Big Data Business Model Maturity Index measures how effectively a company is leveraging data and analytics to drive the business. It provides some immediate benefits. Various companies use various approaches with variable success in their niche.
Any analytic firm of today should focus on building proficiency in data quality and application integration. By implementing new technologies, optimizing the data warehouse will enable the organization to achieve a standardized reporting.