With ever-increasing demand for accurate and consistent data to power analytics, artificial intelligence (AI), and automation initiatives, organizations are quickly moving away from legacy systems towards a modern technology landscape. However, this is a time, cost, and resource intensive process and very often, likely to experience cost or time overruns. One of the most common contributors to these delays and spike in cost is the inability to accurately estimate the transformation/modernization engagement, from an effort and timeline perspective. An additional factor is the lack of a simple way to manage the ETL estate and accelerate the upgrade/modernization initiatives.

Some key questions that developers need to be asking themselves include: Are the deadlines being met? Is the project on-track? Is engineering time spent more on existing processes than on building new ones? Often, the answers to these questions is in the affirmative, which unnecessarily prolongs the activity and probably might even derail it.

What can help pull this together and ensure seamless execution of ETL upgrade/modernization programs is a bunch of features that promise reliability, automation and self-service capability. A comprehensive view of the ETL inventory is quintessential to proper planning. Analyzing and precisely determining job complexities keep the plan realistic and achievable. From an end user point of view, the ability to search for job designs and assess the attributes involved brings a sense of control. The automation employed to analyze source and target connectivity makes life a lot easier for ETL development teams.

As customers are more open to embracing newer technologies, and given the growth and innovation in the data engineering landscape, there is a huge market potential for frameworks and accelerators that address these challenges seamlessly.

The DataStage Analyzer, an accelerator from Wipro, helps customers in their DataStage upgrade/modernization through intelligent discovery and management of the DataStage ETL jobs inventory, leveraging rich and intuitive visualizations. This enables accurate and credible effort estimation to execute cost effective and seamless DataStage ETL upgrade/modernization initiatives.

Organizations are now at an advantage when it comes to simplifying DataStage ETL inventory management. Accelerated due diligence/discovery, as part of the version upgrade/migration/modernization initiatives, coupled with an intuitive visualization to better represent the ETL estate are the two most efficient outcomes of employing the accelerator.