Unlocking the Power of Big Data With Big Data Techniques

Data is generated each when your customers access an email or mobile application or tag themselves on social networks, make a purchase on the internet, contact customer service, or talk to an online assistant. When a lot of data cannot longer fit into classical databases, it is required to make application of big data methods to analyze patterns and gain insights.

Data analysis uncovers valuable information within huge datasets and transforms it into actionable intelligence that can change business processes, provide new opportunities and spur big data techniques innovation. The key to unlocking big data’s potential is advanced analytics, machine learning and AI technologies.

The first step in using big data is collecting it. This includes gathering non-structured and structured data from many sources, including IoT sensor, social media, cloud applications and transaction systems. This requires adjusting traditional methods of data collection, and integrating diverse kinds of data into central repository like the data lake.

Once the data is taken, it needs to be stored in an accessible and cost-effective manner. Big data technologies are based on scalable processing and flexible storage. Big data solutions are usually based on distributed architectures which lower costs and provide fault tolerance. They also support a variety of formats and structures. Some are designed to work with NoSQL databases, data lakes, and schema-on-read technology.

The next step to analyze big data is modeling, a type of pattern recognition and explanation that requires the variables and their relationships to formulate mathematical formulas for them. This method can be more accurate in describing the relationship between variables than other methods.

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