Data Management

 

Transit ETL

Today, many companies' IT departments are dealing with large volumes of data that is spread across various machines, platforms and data sources. Most times, much of this data resides on the mainframe, a complex environment that provides its share of challenges for users needing access to that critical data. Select's Transit ETL allows companies to access this mission-critical operational data and deliver it whenever and wherever needed.

Transit ETL is designed to allow non-technical users to quickly and easily extract data from the mainframe and mid-tier systems (e.g. VSAM, QSAM, IMS, DB2, IDMS, Oracle, and SQL Server), transform the data using over 100 built-in functions and operators, and save the data in one of a variety of formats, including fixed, delimited and XML. Extremely flexible, Transit ETL can be used for one time data migration projects or in daily production jobs utilizing the built-in scheduling facilities.

Select's Transit ETL is the perfect addition for companies wanting to move data from application to application, or from platform to platform, freeing the IT department to work on their core job functions.

 

Data Access

NOMAD is a data management product that can easily access and combine data from a variety of sources including leading relational DBMS' such as DB2 for z/OS and z/VM, Teradata, and IDMS, as well as non-relational DBMS' such as IMS and IDMS. In addition, NOMAD can access QSAM sequential files and is, especially, efficient at accessing the complex hierarchical structures of VSAM files, typically, in use by banking, insurance, and other industries. Data from these sources can be accessed directly through a number of tools we provide.

NOMAD - a Relational and Hierarchical DBMS

Since NOMAD is itself a database management system that can be either relational or hierarchical, data extracted from the numerous heterogeneous systems mentioned above (databases and files) can be transformed, combined and loaded into a NOMAD database. Utilizing built in functions, NOMAD can quickly aggregate or summarize the data where it can be used for further reporting and analysis.

Data stored in NOMAD databases can be in the form of a data mart, operational data store (ODS), or a data warehouse based on the requirements of the organization. NOMAD allows users to combine data stored in a NOMAD data mart or warehouse with live or current data for comparison reporting.

Where a data warehouse implementation tends to serve the entire enterprise, a division or at least multiple departments, a data mart is a repository of data gathered from operational data and other sources that is designed to serve a particular group of users. The emphasis of a data mart is on meeting specific needs in terms of analysis, content, presentation, and ease-of-use. In addition, a data mart often uses aggregation or summarization of the data to enhance query performance.

NOMAD’s data management power stems from the breadth of its language and its unified architecture. NOMAD’s comprehensive data definition language provides extensive support for data types, including arrays and time series, powerful defaults and flexible security and integrity constraints, including full support for rule-based referential integrity.  Equally important, NOMAD’s unified architecture includes self contained procedural facilities that deliver everything expected in a traditional programming language.

Storing the data mart or data warehouse in a NOMAD database allows security at not only the database level but record and field level based on groups and user levels.

Implementing a data mart with NOMAD often can be achieved within a fraction of the time and money of traditional data mart or data warehouse approaches.

For years, NOMAD has been used to simplify large amounts of diverse production data that spans across the enterprise and creates something that is accessible and meaningful to the right audience for improved decision making.


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Useful Links
IBM CICS
IBM DB2
IBM Mainframe servers
Microsoft SQL Server
Teradata