data management

Big business process and data management

Forrester Research first coined the phrase "big data process" in August 2011 to describe the shiift from a fragemented,  siloed approach to business process management (BPM) to a more holisitic approach that stiches all the peices of a prcess together, across an enterprise, to drive enterprirse transformation.

The parallels between their recommendations and those of leading data management experts are no coincedence. The findings yet again emphasise the relationships between data and business process.

Both big process and data management must be driven by business stakeholders. IT simply does not have the mandate to achieve the cultural shifts necessary to really drive either process changes or to embed data quality as a fundamental principle in the business.

The most recent discussion uses the four C's to highlight the relationship between data and prcess.

1.) Customer data is hidden inside "oceans of operational data" that must be mined and cleaned in order to improve the customer experience and underlying business process.

2.) Chaotic business processes can only be resolved with a better understanding of the relationships between process and data.

3.) Context of uinformation is critical. The relationships between business evetns, operational data, and operational performance are frequently misunderstood leading to lost revenue, unnecessary costs and significant operational risk.

4.) The shift to Cloud architexcture frequently overlooks the need to maintain data relationships across a fragmented value stream.

All of these examples are also key drivers for data governance, and critical success factors for large IT projects such as MDM and ERP implementations.

We will be presenting an aproach to address these issues through Process driven data governance and MDM, at the Process Forum, on 6 June 2012, in Johannesburg.  For more information, or to register for this event, click here.

expressor extends big data support with Enterprise Edition

The expressor Enterprise Edition, which was released on 9 April 2012, provides additional capabilities to address the needs of organisations looking for cost effective solutions to handle Big Data. This release improves expressor software’s position as the price/performance leader in the data integration market.

The ongoing proliferation and growth of data sources require companies to adopt a high performance data processing infrastructure to meet their demanding business needs.  expressor Enterprise Edition addresses these big data needs via its patented data processing engine, which provides near linear scalability for parallel data loads.

It does this while enhancing the game changing ease of use and rapid development capability that has made the platform a winner with data centric users that require a simplified approach to the tedious and time consuming tasks typical of most other ETL tools.

The solution can be deployed on either Windows or Linux servers (of any size in terms of RAM and processors) for a single low cost. Similarly, the solution can support any number of expressor Studio development seats. This makes it the industry leader in price vs performance.

Other enhancements released in version 3.6 include significant work to the user interface, the Teradata Parallel Transport Operator which provides really fast data loading for expressor software's Teradata clients using Teradata's Parallel Transport API, and improvements to the upgrade process for existing artifacts.

To download expressor Studio 3.6 click here