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IDOL SPE

Autonomy IDOL SPE represents a radical shift in processing data from the database. The product is a dynamic, self-learning solution that can automatically make connections in the data by understanding the meaning that resides within it.

IDOL SPE transforms the RDBMS into a next-generation probabilistic inference engine by:

Breaking out of a black and white world to understand the "shades of grey" in the data
Rendering "no exact match" a problem of the past by automatically spotting patterns in the data to make accurate predictions and identifying nearness
Ensuring delivery of relevant, personalized results by automatically detecting patterns in data within heterogeneous sources and incorporating information gleaned from users' interactions with the data

Adding Intelligence to the Database

IDOL SPE leverages results from interactions, usage, and datasets to continually refine and perfect understanding of the data space. This self-learning capability is extremely valuable in a business context, as organizations can leverage the insights to continually improve processes, operations, and interactions with customers.

Patterns of Data

IDOL SPE enables computers to replicate the human ability to intelligently recognize and understand complex patterns in data automatically, which can in turn be used beyond the confines of the structure imposed by the source of data. IDOL SPE can thus break out of the restricted scope of the structured query that limits traditional database technologies, and relate n-dimensional structured objects to one another conceptually, even where no direct field match exists or when they belong to entirely different databases.

Patterns of Usage can inform the space

Patterns of Usage

Businesses fail to capture and leverage many user interactions with data in a meaningful way. Only the final transactional behavior is recorded and logged into business applications. IDOL SPE recognizes the importance of user behavior and uses both potential and committed behavior patterns to inform its descriptive space. All user interaction can be incorporated to automatically evaluate community trends as well as individual user trends.

For instance, an airline can leverage IDOL SPE to improve online customer experience and increase sales. A customer searching for a flight from New York to San Francisco at a date and time when all flights are sold out will be automatically offered an alternative nearby airport such as Oakland or San Jose, rather than returning "no results" to the customer's search. IDOL SPE infers the result from patterns in the data and its usage without the need for formulas, scripts, or other means which require prior knowledge of cases and exceptions.

"As organizations renew themselves to come out of a recession, IDOL SPE may be just the sort of disruptive technology they need."
Mike Davis, Senior Analyst, Ovum, 2009

Going Beyond Legacy Technologies

While legacy technologies will likely continue to serve as the predominant stores for structured information, the methods for analyzing this business-critical information is changing.

With IDOL SPE, probabilistic modeling surfaces patterns in the data without prescriptive prior knowledge, and enables these patterns to be used in direct interaction with business functions. This greatly reduces the amount of manual scripting for its creation and maintenance, as well as allowing broad new insights to be illuminated.

IDOL SPE becomes even more powerful and indispensable when complex scenarios with multiple disparate databases are involved. In these cases, IDOL SPE can identify patterns across the sources with no need for expensive data warehouses or BI-type integrations. Legacy solutions are ill-equipped and prohibitively expensive for performing such sophisticated operations.

Recognizing its value in certain cases, IDOL SPE fully supports traditional methods used by BI applications. Simple and complex SQL queries (e.g. FIND, JOIN, ORDER BY, SELECT) can be entered to pinpoint and manipulate search results, or parametric searches can be performed based on defined metadata, as is often done in eCommerce applications.

When no exact match is found, IDOL SPE can automatically relax the query to find near matches

How is IDOL SPE different to Business Intelligence (BI)?

Databases can miss subtleties before feeding information off to be analyzed by BI systems, for example two data sets may produce the same end result; that dog owners prefer dogs to cat owners, however subtleties in the data can be missed. Such as, the cat owners in Set A liking dogs over 80%, but not reaching the 100% match of the dog owners, is not the same as Set B, where cat owners only like dogs 20%. This information could be very useful for an ad campaign designed to target cat owners.

With IDOL SPE it is the data itself, rather than the output of an arbitrary schema or system of logic that is analyzed. This leaves no room for subtlety to be lost. IDOL SPE is able to function as a standalone module or as an add-on to the existing RDBMS infrastructure, to provide answers in response to traditional structured SQL queries as well as probabilistically, applying contextual intelligence to the raw data.

IDOL SPE has diverse applications as it removes the need to create and update complex rules and scripts, or to have a human being in attendance to suggest best alternatives. IDOL SPE allows the enterprise to extract maximum value from structured data and eliminate missed opportunities.

Download the IDOL SPE Product Brief

This is a selection of our forthcoming events, please visit our seminars page for more information.

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This is a small selection of the Autonomy case studies available, please visit our publications site at http://publications.autonomy.com/ for more information.

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Products KeyView IDOL | IDOL SPE
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