All articles tagged with #unstructured data
A 19-year-old entrepreneur, Dhravya Shah, has developed Supermemory, an AI memory API that enhances long-term context understanding by extracting insights from unstructured data. The startup, backed by $2.6 million in seed funding from notable investors, aims to serve various AI applications by providing a high-performance, low-latency memory layer, positioning itself as a versatile tool in the evolving AI landscape.
Snowflake has launched Document AI, a new interface that uses a large language model (LLM) to extract value from unstructured data. The interface processes natural language queries to extract content and analytical insights from documents such as invoices and contracts. The converted data can be used for traditional analytics, BI or other downstream ML processes. The move marks a major development for the data giant, which started off with a focus on structured data. Snowflake also announced updates for Iceberg tables and ML-powered SQL functions for its data cloud, as well as cost optimization tools.
The subreddit r/dataisbeautiful showcases easy-to-understand visualizations that effectively convey complex information. Data analysts can identify and address data quality issues in large datasets by employing strategies such as data profiling, cleaning, imputation, and validation. Organizations should look for data analysts with problem-solving skills, proficiency in programming languages and software, statistical analysis, machine learning knowledge, data visualization ability, and communication skills. Unstructured data requires additional care, and organizations should foster a data-driven culture while keeping in mind the ethics of data collection, usage, and storage.