Advanced and Ad-hoc Data Exploration, Analysis and Discovery
Easy To Use Without Significant Technical Expertise
With Insight, Xpriori’s discovery and analysis tool, an end-user can explore all information in an iterative, intuitive and visual way in real time with no database programming required. No data cubes need be created. The product supports highly interactive drill down/drill around analysis, which, in turn, enables ad-hoc exploration and on-the-fly analysis of heterogeneous data sets such as corporate sales data, public and industry data to the discovery of significant patterns, relationships and behavior. Once the initial analysis is completed, users can monitor scenarios on the fly with customizable gauges on executive dash boards.
The analysis is heuristic. Coupled with XML enabled forms from Adobe and Microsoft, one moves immediately from data gathering to analysis. No need to have an expert create hypotheses, one can rely on what the data tells you directly.
Business users are able to query their information without the involvement of technical personnel. As a result, they can discover factual correlations and business intelligence that would require significant time, technical expertise and expense with traditional methods and tools. Users need not have significant a priori domain knowledge. They can discover important aspects of information that have remained unknown because of database complexity and the inability to analyze data and metadata relationships dynamically.
Why Insight Works: For A More Technical Reader
Insight, an ad-hoc data exploration, analysis and discovery tool, enables rapid analysis and decision making with zero programming. The ad-hoc model of Insight breaks the traditional mold and creates a new paradigm in information analytics. When compared to traditional formalized statistical analysis, Insight provides significant value through reduction of cost and time to decision. Insight leverages the highly efficient pattern-matching core technology of the XMS native XML database to enable high-speed information analysis. The XMS database eliminates any need for costly star schemas, or data cubes. Because XMS processes XML information on the fly and without requiring schema definitions, Insight can immediately consume and analyze heterogeneous data stored in XMS, support high speed and ad hoc N-Dimensional Analysis.
Insight Is Heuristic vs. Deterministic
Formal statistical analysis tends to be algorithmic. An algorithm is a complete set of mechanics for solving specific problems and implies a-priori concepts of the expected answers. Although it uses algorithms, Insight implements a heuristic analysis model. A heuristic is an incomplete set of guidelines with the potential for leading to greater learning and discovery. By allowing the analyst to work in a heuristic manner to perform ad-hoc exploration, Insight enables the discovery of previously unknown information that might otherwise remain hidden indefinitely.
The analytical model leverages the pattern-matching core technology of XMS. Highly efficient pattern-based set intersections performed by XMS enable the ad-hoc drill-down/drill-around and discovery capabilities of Insight. Because the analytical algorithms do not require conformance to rigid rule sets, Insight can compute correlations and display the results on the fly. The high-speed analytical capabilities of Insight provide for immediate inference and decision-making. By allowing the analyst to work in a heuristic manner to perform ad-hoc exploration, Insight enables the discovery of previously unknown information that might otherwise remain hidden indefinitely.
Significant Advantages To Traditional OLAP (on-line analytical processing) and DM (data mining)
In enterprise information analytics, the Insight analytics model bears some resemblance to traditional OLAP (on-line analytical processing) and DM (data mining). However, Insight provides significant advantages over the OLAP and DM paradigms. Data mining and OLAP are non-equivalent, complimentary technologies. Insight uniquely implements some necessary OLAP and DM features and renders others unnecessary. Industry efforts to integrate OLAP and DM indicate a trend in the information analysis industry toward the Xpriori Insight model.
OLAP belongs to a sub-set of decision support tools used to discover patterns and relationships in a data set. The user forms a hypothesis about a relationship and verifies it with a series of queries against the data. In other words, the OLAP analyst generates a series of hypothetical patterns and relationships and uses queries against the database to verify them or disprove them. As such, OLAP analysis is a deductive process. An OLAP database is often synonymous with a data warehouse and typically constructed using star/snowflake schemas, or data cubes.
While OLAP databases enable analysis of n-dimensional data sets, the time associated with hypotheses development and data cube design results in a high cost compared to Insight. XMS supports dynamic and hierarchic heterogeneity without schema design, or re-design. Insight adapts to the XML structure based on its inherent context regardless of the existence of heterogeneous structures within a given data type. In other words, Insight and XMS view heterogeneous data sets of a given type in a manner similar to the abstraction concept of object oriented software design. This enables Insight to quickly analyze n-dimensional data sets without any need for data cube design and de-normalization, as with OLAP.
Traditional OLAP and data mining methods use separate approaches to finding patterns and relationships within data sets. OLAP methods involve hypothetical query construction and data manipulation (data cubes). Data mining methods use database queries to retrieve data before applying a variety of statistical and artificial intelligence algorithms. Insight realizes a superior advantage over traditional methods by leveraging the core pattern processing technology of the XMS database. The native pattern-processing capability of the XMS database engine virtually eliminates any need for data cubes and external statistical analysis for identifying patterns and relationships.