Big data, as we now know, is not a fancy term anymore. It’s just getting bigger with each passing day as the number of companies multiplies, and competition becomes fierce between these businesses. The sheer amount of data that these companies generate needs to be harnessed effectively for the benefit of the organization.
Organizations have a lot to do with the data as it helps them in making the right decision to generate good revenue and profit. Big data, which is the collection of all the structured and unstructured data, with the help of artificial intelligence, can help organizations in deciding the best opportunities for their business. Both of them need each other to bring out the most meaningful insights. Big data gives the platform to AI for interpreting the data, while AI personalizes each of the data suitable for the organization.
How AI does it?
Let’s unravel the technique behind it:
AI tools have the power through which it can empower the businesses in micro-targeting the customer journey throughout the entire cycle. It does with an Omni channel approach, which is near to impossible for a human being. It can even help in planning the content and delivering by matching the purchase history, search queries, and the emerging market trends. Both AI and big data complement each other to generate the best results for an organization.
There is an explosion of data in all the industries; the same has been observed in the scientific world. For example, the CERN data center, the organization which discovered the GOD particle called Higgs Boson, has accumulated over 200 petabytes of filtered data. With the advancement of AI and machine learning, the data can lead to major breakthroughs.
AI can help to filter hundreds of millions of the collision events of the particles each second for finding the most interesting one. It will further execute research on this for spotting the pattern. The data monitoring on the industrial control systems at the CERN can help to prevent faults before they even arise!!!!
Have you heard about data modeling?
It is a science that helps in organizing corporate data to fit the needs of an organization. It needs designing logical relationships for data to interrelate with each other.
The AI-powered analytics helps the businesses in scenarios such as WHAT-IF for accuracy. It helps to predict the future, for example, how a new product is going to perform in a new market and the number of opportunities one can explore in the later stage.
Data modeling is partially automated and partially manual. It offers more control and power to data crunchers. The process is the foundation of all cognitive computing technologies.
Some of the useful tips for big data modeling:
- Not to impose traditional modeling techniques on the big data
- A system has to be designed not the schema
- Searching for the modeling tools
- Focusing on the data essential for a specific business
- Delivering quality data
As per a Gartner study, some of the characteristics for machine learning and AI platforms are summarized:
- The higher the data, the better is the learning process
- For the data pipelines to work in a machine learning environment, data architecture has to be designed for working with the basic data platform.
- Modeling big data samples is an arduous task, but huge improvements are underway.
Both AI and big data need to work together so that organizations can implement actionable insights in their process. With artificial intelligence having the natural ability to unify and process a large amount of information, the tool helps businesses in putting insights into work.
These two technologies have the power to make human lives better while also making the process easier for companies worldwide.