Business’ today generate vast amounts of data. All data has patterns that can provide valuable insights. Machine learning startups are taking on many of business’ most significant challenges to make sense of their data. Machine learning is being deployed for heavy lifting of this data to make it actionable.
Silicon Valley, California based Alation offers a machine learning data catalogue to help people find, understand and trust data across their organizations. Alation’s solution aligns with the requirements of Chief Data Officers, Analysts and Data Engineers. Their Data Catalogue is known for its usability and intuitive design. More than 100 organizations, including the City of San Diego, eBay, Munich Re and Pfizer have adopted the Alation Data Catalogue.
All data has inherent patterns. Start-up Anodot capitalizes on the innate strengths of machine learning by continually looking for patterns using constraint-based modelling across the diverse data sets, businesses are relying on to operate daily. Similar to many machine learning startups that capitalize on the technology’s ability to learn continually, Anodot’s AI platform looks to eliminate blind spots in data and quantify root-elements in diverse data sets. Anodot’s Autonomous Analytics platform leverages advanced machine learning techniques to constantly analyze and correlate every business parameter, providing real-time alerts and forecasts.
Data consumes space and storage can be expensive. Data can be compressed without loss of information. Compression.ai is relying on machine learning to improve the encoding and decoding densities achieved for images, averaging 95% compression rates of a raw image without significantly losing its quality. The algorithm uses deep neural networks to create a representation of the image, a technology the company calls it Machine Learning Visual Extension. This extension creates a compressed representation in an entirely new file format that has intelligence embedded within the file structure.
Dataiku has designed and launched their Data Science Studio platform to aggregate the steps needed to transform raw data into data-driven applications that are easy to maintain. The Studios’ workspace is designed to be intuitive, interactive and capable of shortening load-prepare-test-deploy cycles required to create data-driven applications. Their customers include Unilever, GE, FOX News Group, Palo Alto Networks, SAP/CallidusCloud and many others who use Dataiku to gain higher intelligence and insights from their massive data sets aggregated over decades of operations.
Data startups are providing tools to businesses to capture the generated data points for business growth.
Credits : Akhil Handa,Pankaj Tadas