Maana Redefines Big Data Analytics to Optimize Key Assets & Business Processes of Fortune 500

Receives Patent for Unique Semantic Search Technology and Introduces Enhanced Platform with Flexible Knowledge Modeling, Advanced Analytics, New UI

PALO ALTO, California — December 15, 2015 — Maana, the analytics platform that operationalizes big data insights into line-of-business applications, today announced further enhancements to its software, making it the most powerful end-to-end platform for discovery and operationalization of big data insights for Fortune 500 companies. Maana takes a fundamentally new approach to big-data analytics by using its newly patented Emergent Semantic Graph and unified index strategy to search across all data silos and data types. Maana’s user-guided, machine-assisted approach makes it easy and intuitive for users to find and draw correlations between data from disparate sources in the context of the asset or business process to be optimized. The platform uses Apache® Spark™, which supports advanced machine learning algorithms and distributed compute. Today’s announcement introduces major enhancements, including: flexible knowledge modeling, advanced analytics, operationalization of data mining models, and a highly intuitive UI to easily navigate descriptive statistical analysis.

Using Maana, Fortune 500 companies can organize their siloed data into new knowledge for discovery and operationalization of insights. Going beyond data discovery, Maana brings big data insights as recommendations directly into line-of-business applications to enable thousands of employees to make smarter day-to-day decisions.

“By providing a more holistic view of assets and business processes, enterprises are now able to gain unparalleled insight into optimizing those assets and processes,” said Donald Thompson, founder and chief technology officer at Maana. “Many of our customers have turned to Maana after trying multiple technologies and solutions. They selected Maana because it is the only software platform that rapidly solves the most complex data analytics challenges of Fortune 500 companies without requiring an army of professional services experts and data scientists.”

Working with a Fortune 50 company that sought to optimize accounts receivable collections without increasing collector headcount, Maana improved A/R collections by 65 percent over the prior year. Maana crawled and mined historical data, identified the factors that affect late payments, operationalized call queue insights in the collection system, and provided on-going recommendations that helped maximize A/R collections.

The Most Comprehensive End-to-End Big Data Analytics Platform

Maana’s end-to-end analytics platform enables enterprises to analyze data in multiple silos  simultaneously, allowing them to dramatically accelerate – from months to days – the time it takes to get from raw data to continuous insights.  These insights optimize key assets and business processes of Fortune 500 companies, which can translate into millions of dollars in increased profitability.  Maana’s recent enhancements make the platform even more comprehensive by including:

Flexible Knowledge Modeling (with or without ontologies)

  • Emergent Semantic Graph: Creates a continuous knowledge structure of assets for iterative insight discovery
  • Assisted Modeling: Organizes raw data into meaningful, flexible, overlapping categories (without re-indexing)
  • Ontology Support: Maana doesn’t require ontologies (i.e., it is statistically semantic), but ontology support is provided
  • Knowledge Representation: Powerful model that integrates structured, semi-structured, unstructured, time series, sensor, events, multimedia, and categorical information – all from multiple sources
  • Powerful Query Language: Similar to SQL but supporting graph operations, data reshaping, arbitrary calculations, and transformations – all at massive scale

Advanced Analytics

  • Continuous Insights: Continuously updates insights with incremental data sources and updated data
  • Temporal Co-occurrence: Finds relationships between events that happen together in time
  • Temporal Clustering: Clustering of temporal entities based on configurable distance metrics
  • Auto-parsing: Automatically converts unstructured log file data into structured data
  • Topic Modeling: Identifies topics that describe text fields and clusters the results
  • Similarity Search: Finds similar entities based on exemplars and a set of user-defined features 

UI to Interactively Navigate Descriptive Statistical Analysis

  • Introduction of Notebooks, advanced filters, and connected search to support data modeling and analysis from the UI
  • Compare Entities and groups of Entities on the basis of shared aggregate measures

Operationalized Deployment of Data Mining Models

  • Operationalize into Business Applications: Maana’s APIs and extensible Custom Answer Service enable line-of business applications to harness insights for thousands of employees to make better decisions
  • Adaptable Insights: Maana’s model is aware; it learns from the actions of the subject-matter experts and adapts
  • Executive Analytics: Measures the improvement on an organization’s KPIs, that results from Maana’s ongoing operational recommendations

 

About Maana:

Maana organizes the world’s industrial data and human expertise into digital knowledge to enable millions of experts to make better decisions affecting the global economy and human civilization.  Using our Knowledge Platform™ and its proprietary Computational Knowledge Graph™, Fortune Global 500 industrial companies drive answers to operational questions that direct the future. Operating internationally, Maana is a privately-held company with offices in Menlo Park, California; Bellevue, Washington; Houston, Texas; London, UK; and Dhahran, Saudi Arabia.

 

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Jeremy McKeon jmckeon@maana.io

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