Significance of Automation Tools in the Data Integration Industry

 

 Increasing number of companies are turning to decision support systems, CRM and various other enterprise solutions to sharpen their business intelligence using business data. However, the not so dependable data is proving to be a stumbling block to Business intelligence (BI) solutions. Companies are investing heavily in data warehousing processes, but the results are far from encouraging. In many cases, mishandling of the data migration process is among the main causes of business intelligence failure. As a reason, a number of business intelligence projects remain non-starters for the want of a complete solution for data integration.

According to 2015 Gartner magic quadrant for data integration tools, Informatica has been positioned as a leader and leads the way among its competitors in most of the aspects of data integration industry. Informatica is the most trusted ETL tool that has made data integration and data migration an effortless process besides helping enterprises manage, bulk amounts of data swiftly and effectively. Though the ETL market is crowded with competitors but Informatica remains a formidable player. It has only one thing on its plate and that it is data integration which helped it maintain its leadership position in the crowded ETL tool market.

When someone talks about problems migrating from existing ETL platform, they're just not talking about integration issues alone. This includes concerns about data discovery and data mapping also known as Pre-ETL source to target mapping, which are equally important. Creating source mappings is achieved using spreadsheets or other homegrown solutions. Often the legacy process involves copy pasting of the information and feeding it to excel sheets or spreadsheets. The entire process is replete with manual intervention and hence involves a lot of time-taking procedures and prone to human errors. It is no wonder that data inconsistency is among the key problems facing the pre-ETL process.

Needless to say, migrating ETL jobs from one ETL platform to another is time consuming and error-ridden process. Automating most of such conversion processes may often be looked as the optimal solution for such requirements. Automating pre-ETL processes will help organizations reduce costs, efforts and time. There are a number of applications available that are designed to convert legacy ETL tool transformations of the new ETL tool platform. These applications complement the pre-ETL process by helping manage the data mappings. But the real challenge is creating comprehensive code which generally demands quality time and should be in compliance with standards. A misstep can lead to productivity inefficiencies because this process needs manual intervention extensively. But all this is a thing of past, as it is no longer needed to depend on manual coding. Thanks to the automated code generator that is designed to automate manual coding and scripting ETL jobs. It can auto generate ETL jobs for any ETL tool like Informatica. This to a great extent cuts costs by automating and standardizing DDL creation, Test Cases and Test SQL. Further it can generate source to target data mappings.

Data driven organizations are constantly updating their system landscape, technology and methodologies to stay in tune with the changing business scenarios. The huge amount of data generated from multiple sources and in variety formats necessitates a well-defined data integration model that will not only help avoid data discrepancies, but also removes barriers to enterprise business intelligence. Data migration, data integration and dependable data are key success factors for the effective implementation of BI.

For those who have not yet explored the benefits of metadata management, Informatica and code automation framework makes a winning combination to move from excel based mapping.