|By Adam Wilson||
|March 31, 2012 01:00 PM EDT||
Sustaining applications in the most cost-effective and efficient fashion is the foundation to maximizing a return on data. But it is only the foundation. Organizations have to move beyond sustaining applications to driving innovation, and the first step in that progression is learning the best ways to enhance existing applications and implement new applications that will help modernize business processes and support business agility.
The challenges around enhancing applications are well agreed upon. The top challenges include:
- Insufficient Data Quality - Data quality issues of one degree or another are pervasive in the majority of enterprises, leading users to distrust the data. This is a problem within applications and, even more so, across applications.
- Right-Time Access to Information - The pace of business continues to accelerate, and users can no longer wait weeks or days for information necessary to perform their jobs. If business users need immediate access to fresh and trusted information in the applications they use every day, IT must find ways to provide it.
- SaaS Sprawl - As more and more applications move to the Cloud, IT needs to be proactive in maintaining visibility and control over SaaS applications and their data, including the ability to easily integrate them with on-premise applications. After all, "no software" does not imply "no integration."
- Successful Data Migration to New Applications - As organizations implement new applications, existing data must be moved quickly and smoothly to the new apps, on time and on budget, so that dependent business processes are not negatively impacted.
Building Trust in the Data with Automated Data Quality
The core reason why business users lack trust in their data is because that data resides in data silos across multiple systems and, when it is delivered to them, it is all too frequently inconsistent, incorrect and incomplete, not to mention late. This impacts both day-to-day data usage as well as strategic usage. For example, Procurement processes need consistent and correct data on vendor price and performance in order to negotiate favorable contracts, as well as data that is timely in order to either drive or block purchase requisitions and payments to vendors per their adherence to their contracts.
Hence, the first step to modernizing business processes is to enhance application quality with trusted, authoritative data that is predictable, valuable and timely, regardless of how many source systems it is being drawn and integrated from.
Integrating data quality processes into the overall enterprise data integration process is a definitive step for any organization looking to build user trust in their data. This is as simple as introducing automated data cleansing that can be leveraged by all applications across the company. A further step is introducing proactive data quality monitoring capabilities into the hands of data owners, so they participate in improving the quality of their information.
The payoff comes with users spending less time reconciling data and more time working with it.
Ensuring Right-Time Delivery with Data services
Ensuring that the right information is delivered at the right time to the right person is another formidable challenge, but one that can be solved, and data services provide the solution within the context of a service-oriented architecture (SOA). Traditional SOA approaches lack a data integration layer. Anything that cannot be handled by a simple Web service, such as complex data transformations or data cleansing, requires hand-coding and proprietary interfaces, which are things one wants to avoid.
Data services, on the other hand, present a discrete set of sophisticated data integration tasks that support the entire data integration life cycle. These data services can be readily consumed as Web services by the various components of a SOA, and also by composite applications and portals. The complexity of the task is hidden, plus the data services can be easily published to SOA registries and repositories.
Results? Organizations using data services have reported up to five times faster delivery of new data, and cost savings of up to three times. This means that these organizations are able to respond faster to changing information demands, increase IT project success rates, and even deliver comprehensive single customer views on-demand to help drive new revenues and increase customer satisfaction.
Soaring with the Cloud - "No Software" Doesn't Mean "No Integration"
SaaS application spending, as everyone knows, is soaring. As a result, more and more companies need to find ways to support hybrid IT infrastructures that span cloud and on-premise applications and make them work seamlessly together to maximize the return on all enterprise data. And this requires data integration.
Cloud applications have to integrate with other systems in order to provide full value. At the same time, integration needs to happen in a secure fashion lest IT lose control of enterprise data assets. Fortunately, appropriately designed cloud data integration will support hybrid IT environments, essentially by extending unified, enterprise-class data integration services to the cloud.
Things to look for when supporting hybrid IT include a "secure agent" that provides the ability to create and securely manage all aspects of integration jobs, which can be shared between on-premise and cloud deployments. While the agent can be invoked via a web browser, what it does is establish a secure connection between data source and data target and all data integration processing occurs on-premise in the enterprise environment for maximum IT control.
Ensuring the Success of New Applications Through Efficient Migration
As organizations modernize their systems and business processes, they find that migrating data to their new applications is not usually a slam dunk proposition. All data migrations are inherently risky and subject to the lack of suitable tools, skills, knowledge of the data, and an access, validation, and audit strategy. Moreover, there is a lack of tools and processes to help business stakeholders and data users ensure and verify that the data is actually fit for use.
Having the right technology platform and skills goes a long way toward ensuring an on-time and on-budget migration. Knowledge of the data that is being moved is critical to each step of the migration process and ultimately is key to ensuring that the migrated data actually "works" in the new application. Having an infrastructure that supports change during the migration process is mandatory. And active business involvement is the hallmark of every successful migration. Hand-coding, using the wrong migration methodology, and relying strictly on IT are all pathways to migration time and money overruns or outright failure.
In selecting a migration platform, you want to ensure it provides:
- Connectivity to the broadest range of environments and databases
- Built-in data quality profiling, cleansing, and transformations (for all data types)
- Fast, easy development, updating, and reuse of transformations
- Easy auditability of the data from source to target
From Application Enhancement to Business Transformation
The above steps, from building trust in data to ensuring the success of new applications, all speak to enhancing applications to drive business process modernization and business agility. The next leap is to transform applications and, by extension, to transform the business, to drive innovation and growth. Much of what is accomplishable to enhance applications is leveragable when transforming them, but there are also new and highly valuable things to accomplish, as will to be seen in Part 3 of this article.
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