TimeXtender Revamps TX DWA with Machine Learning and Intelligence Capabilities

By CIOReview | Friday, October 23, 2015
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REDMOND, WA: To enable organizations get their business intelligence done quickly and efficiently, TimeXtender- a provider of data warehouse automation (DWA) platform is launching an updated version of its DWA product for Microsoft SQL server ‘TX DWA’ with machine learning and intelligence capabilities.

TX DWA is a Business Intelligence solution which aims to automate labor-intensive and time consuming tasks, minimizing implementation and operation cost. It generates and builds ETL code, project documentation and OLAP cubes. The revamped product came with enhanced features to help data warehouse developers receive reporting and analysis straight from a data warehouse and improve speed, performance and execution for numerous DWA tasks.

The new machine learning and intelligence function for Microsoft SQL Server, eliminates the ongoing need by developers to optimize the solution, resulting in faster load times and stronger efficiency. TimeXtender has also added several other automation functions in the new TX DWA including, Aggregated Tables to enable create aggregations that are saved along with the source table in the data warehouse, Data Access Control at the data warehouse level, Prioritization to let users to give priority to certain tables and sources, Maximum Simultaneous Data Transfers which one source from reducing the performance of the entire execution process and Safeguards for System Errors and Critical Errors.

The upgraded TX DWA product offers easier connection to new data source and many of the calculation tools which are needed by applications to interpret how all data in the data warehouse fits together, and formulates the relationship between tables so that they can understand each other.

In addition it also offers functionalities such as, time dimensions which contains indexes to easily compare historical data with present data, customer periods to track data for seasonal or cyclical patterns to analyze and report, project variables to allow developers change the same value in multiple places, Context Sensitive Variables to handle different development environments and dynamic perspectives that can be developed based on a function such as sales, production or finance to provide an instantaneous overview of all objects related to particular area.