Applications in business are being transformed at a faster rate than any time in history. According to the 2013 Cisco Global IT Impact Survey, 71% of companies report IT is deploying more applications than in 2012. Applications and user expectations are becoming more complex.
Integration is part and parcel of application transformation. It is important that the new systems talk to existing systems and vice versa. According to Gartner, organisations will spend one-third more on application integration in 2016 than they did in 2013. Furthermore, by 2018, more than 50% of the cost of implementing new large systems will be spent on integration.
Whatever reasons an organisation may have for employing application transformation, one of the most critical parts of any such initiative is successful data migration, says Richard Firth, chairman and CEO of MIP Holdings.
“Such a migration can cost as much as R9.3-million, and if the migration forms part of larger project, which it invariably does, you can expect to pay around R30-million. What’s more, is project overruns can amount to around one-third of data migration costs and the sad reality is, these types of projects almost always experience significant cost overruns.”
Because application transformation, and by association data migration, can result in such costly outputs for organisations, it is critical that the projects be handled correctly, he adds.
“It is definitely not an initiative that should be rushed. However, if done correctly, the benefits can be transformative. There are some best practices for managing data in application transformation that can help any company on its way.”
* Understand the process and its inter-application dependencies – if you don’t understand how data flows through your organisation and how its dependencies work, you’re heading for failure during an application transformation.
* Ensure clean data and standardisation – it is critical to clean and standardise data before you attempt to transform your application. You can employ data profiling and data quality tools, as well as data migration tools to help you achieve this.
* Avoid data lockdown – during the design of your new application, build in transparent data access and integration points. Data lockdown occurs when data is isolated in an application silo and can’t be shared easily with other applications, and with today’s real-time access expectations, data lockdown is not an option.
* Sync with most current existing apps and data warehouses – when the time comes to populate a new application with data, you want to ensure the most current data is being migrated. You need to synchronise all relevant data from existing applications and data warehouses before migrating it to your new, transformed, application.
* Define data retention and privacy requirements – planning ahead for a cost-effective and efficient data classification strategy is imperative during an application transformation. Current regulatory compliance standards may require that the data currently stored in those applications may need to be archived and stored for a longer length of time, such as in the new Protection of Personal Information Act.
* Leverage an automated test data provisioning process – testing is an essential part of the application transformation process. It’s also the most time-consuming and expensive. Development and testing takes the most amount of time when developing a new application, consuming 24% on average of the entire application development lifecycle, according to Gartner.
* Using an automated solution will eliminate manual processes in favour of self-service ones. You not only get significantly improved test data quality, with fewer errors or defects, but do so at dramatically reduced costs.
* Leverage MDM – leveraging Master Data Management (MDM) to provide a consistent single source of enterprise master data for current and future transformation initiatives will greatly benefit the process. Remember, migrating data is never a one-time event. MDM helps enterprises minimise risk and speed data migration.
* Know your team and their tools – managers in charge of application transformation projects must get to know their data integration teams, be aware of their skills sets, and understand the tools they will be using for the integration.
* Consider legacy application shutdown – don’t allow redundant applications to run in parallel. Once you have transformed your application, whether through consolidation, upgrade, or retirement, shut down the old one. Users will only adopt the new application if the old one is no longer available. Besides, the costs associated with keeping legacy systems running can be exorbitant.
* Practice smart partitioning – data volumes are, and will continue, to grow. And enterprises struggle to keep application performance at an acceptable level to users given this velocity of data growth. Smart partitioning involves physically organising data in the database to optimise performance. It also streamlines archiving of data as it becomes less relevant to the business.