Big Data Analytics expands your analytical insights

Software

Big Data Analytics

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The use of Big Data is becoming a leading means of competition and growth for companies. Angoss software products support the growing types and volume of data that can be analyzed.

Hadoop can be used as a data source and as a deployment platform for models created in KnowledgeSTUDIO. Data scientists are able to import and prepare massive amounts of data—both structured and unstructured—into memory with 64-bit addressing; and to perform in-database analytics using extremely large datasets and numbers of predictive variables so data can be mined and analyzed faster and more accurately.

KnowledgeREADER includes In-database analytics for text analysis and its data mining and predictive analysis capabilites. KnowledgeSEEKER and KnowledgeSTUDIO users can use the optional In-Database Analytics driver to perform analysis within their enterprise data warehouse. In-database analytics supports Big Data analytics by performing the complete analytical life cycle within massive parallel processing and enterprise data warehouse environments. 

In-Database Analytics performs data mining and predictive analytics directly on data stored in a database as opposed to working on a copy of the data. A key element of this process is that summary information only is extracted from the database, which is then used to drive many elements of the Angoss data mining functions.

In-Database Analytics offers many business performance improvements:

  • Duplication of data between the data warehouse and the analytical processing environment is eliminated.
  • Computation-intensive data mining algorithms (e.g., decision trees and data exploration) are performed on a well-tuned and managed database engine deployed on powerful servers.
  • Data security, integrity and standardization are maintained through one version of the data for all analytical and reporting functions.
  • There is no delay between data acquisition, preparation and analysis within the data warehouse.

Supported In-Database Analytics Features – Angoss’ In-Database Analytics driver supports KnowledgeSEEKER and KnowledgeREADER functionality and core KnowledgeSTUDIO features such as:

Data transformations and scoring and validation for Decision Trees and Strategy Trees are all enabled from within the database. Angoss enables complete analytics workflow within the database—from model development to deployment.

Angoss’ In-Database Analytics driver supports Teradata®, Microsoft® SQL Server, Oracle® and Netezza™ databases, with native open database connectivity (ODBC) drivers required for each of these databases.