Data Storage

Why You Should Use Graph Analytics for Big Data?

Graph analytics has been on a constant rise since the last decade, and there is no stopping it. It is an unparalleled aid to build, understand and analyze company relationships. Before cloud computing became a reality, it was challenging for businesses to imagine graphic representation. With the advent of graph analytics, the analysis of business-oriented data has become more accessible and secure. In her article for ‘Tech Target,’ Lisa Morgan shares why you should use graph analytics for your company.

Is Graph Analytics the Future?

Graph analytics uses algorithms to configure the relationships between a company’s interconnected database and analyzes them to produce a graph-based analytical result. It is primarily used to prevent detection fraud, or establish relations between different business lines, and search engine optimization. Mark Beyer, Vice-President at Gartner, asserts that it is essential for businesses to provide a flexible computing environment for graph analytics to perform well.   

Know Your Business

Ramesh Hariharan, CTO and head of data services at LatentView Analytics, observes that using graph analytics for big data can assist the company in faster decision-making and precise automated decisions. Another thing that Hariharan mentions is product trend forecasting. Consumers create many trends where some of them might not grow popular. Graph analytics helps companies put things in the proper perspective and explore the data to acknowledge new trends and act accordingly.

The rise of data management and analysis began close to 2019. Back then, metadata and analytical figures were supposed to answer a specific set of questions that didn’t provide graph analytics with a flexible environment. Companies wanted to get detailed information and put it to use. It was predictable and stale. With the pandemic, the unpredictability rose to an unprecedented scale, and it has changed the way graph analytics functioned.

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