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Using Text Mining on Reviews Data to Generate Business Insights!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Textual data from social media posts, customer feedback, and reviews are valuable resources for any business. There is a host of useful information in such unstructured data that we can discover.

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How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

The pathway forward doesn’t require ripping everything out but building a semantic “graph” layer across data to connect the dots and restore context. However, it will take effort to formalize a shared semantic model that can be mapped to data assets, and turn unstructured data into a format that can be mined for insight.

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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats. However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. He holds a PhD on data management in the cloud.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

How is it possible to manage the data lifecycle, especially for extremely large volumes of unstructured data? Unlike structured data, which is organized into predefined fields and tables, unstructured data does not have a well-defined schema or structure.