Big data is a phrase that the industry coined in 1987, but it took years before it became truly popular. By the time the name was a household term, big data was everywhere, and companies were seeking ways to store and use the data. Data scientists knew that big data could hold valuable insights. The key was finding a way to analyze it as it continued to flood in constantly.
Sifting through and parsing the data into a format that data scientists could work with was a big task and too much for the average person to handle. Artificial intelligence holds the key to pulling insights from these enormous volumes of data.
That’s not to say that data scientists will become obsolete anytime soon as there’s still a human element in reviewing insights AI has put together.
Integrating AI into databases is the future for making big data useful to businesses. Businesses have discovered tons of applications for AI and big data, including improving geolocation technology. Data is coming from all sorts of devices now, including smartphones, tablets and IoT devices.
The Role of AI in Big Data
As the internet continues to offer more ways for companies to interact with their customers, consumers generate more data day by day. Big data can include the following data points.
- Customer likes and dislikes
- Consumer habits
- Activities or actions within an application
- Social media activity
- Product reviews
- Loyalty or reward data
- Online profile information
Collecting and parsing this information can make it useful and AI offers learning capabilities to recognize trends and adapt customer interactions accordingly.
As such, AI and big data are becoming inseparable from one another. But you also need a good database foundation to ensure that the data the AI is reading and learning from is good, accurate data.
Databases in the Big Data Era
Big data has changed more than just how we analyze data. It has also changed how we store and process data. You will be probably be surprised to know how much big data has proliferated. In 2020, the average person created 1.7 megabytes of data every second. Because the volume of data that a company handles continues to increase rapidly, so must the company’s database capacity increase.
As such relational databases are slowly falling out of favor and NoSQL databases are rising in popularity because they offer the opportunity to use database sharing to spread data across many economical servers or machines.
Relational databases only scale vertically, which can be quite costly to store the many types of data necessary. In NoSQL databases, the data does not follow a structured format like SQL, making it easier to store.
Therefore, NoSQL databases with integrated AI are the ideal solution for handling the ongoing demand for handling and analyzing big data.
How AI in a Database Aids in Understanding Big Data
AI and big data are perfect for one another. As your database ingests new data, artificial intelligence goes to work parsing the data.
The more data AI parses, the smarter it will get and the more benefit it will offer your company. You’ll get more out of your data and make your data an asset. But first, you have to understand your data, which AI can help you do.
To harness the power of AI, get a NoSQL database like BangDB where AI is fully integrated instead of moving the data to an outside service to parse and understand it.
The post Artificial Intelligence and the Future of Databases in the Big Data Era appeared first on SmartData Collective.
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