Unlocking the Power of Big Data With Big Data Techniques

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Data is generated every time your customers use an email or mobile application, tag themselves on social networks, place an order online, contact the customer service or talk to virtual assistants. When a lot of data cannot be accommodated in traditional databases, it is required to make application of big-data techniques to identify patterns and gain insight.

Data analysis uncovers valuable data in massive data sets and transforms it into actionable intelligence that can transform business processes, reveal new opportunities and spur innovation. Advanced analytics, machine learning and AI technologies are crucial to unlocking the power of big data.

The first step in using big data techniques is collecting it–a process that includes gathering structured and unstructured data from various sources like IoT sensors and social media cloud applications, and transaction systems. This requires a modification to the conventional data collection process and integrating disparate data forms into central repositories like data lakes.

Once the data has been collected it must be stored in a cost-effective, accessible manner. Big data technologies are based on scalable processing and flexible storage. Big data solutions typically use distributed architecture, which helps reduce expenses and allows for fault tolerance. They support a wide variety of formats and structures. Some are designed to work with NoSQL databases data lakes, data lakes, and schema-on-read technologies.

The next step in analyzing big data is modeling, a type of pattern recognition and explanation that uses an array of variables as well as their relationships to formulate an equation for them. This method can be more precise in describing relationship between variables than other methods.

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