1024RA Cloud-based Data Integration Changes Business for Enterprises and Providers

What is Happening? This week Informatica, The Data Integration Company, held an invitation-only, two-day conference for a select group of industry analysts at a hotel near the company’s Redwood City, California headquarters. While Saugatuck’s head of research, Bruce Guptill attended the full program of conference events, I conducted an interview with two senior executives at the information management company on the subject of data quality, data governance and the Cloud.

Full Disclosure: More than twenty five years ago, I managed data administration at John Hancock and later at Fidelity Investments, founded the Boston chapter of the Data Administration Management Association (DAMA) and was deeply involved in the issues of data quality and data governance in a number of vendor user conferences, including IBM GUIDE.

Not only are these issues not new, the challenges have grown ever more complex with the proliferation of architectures and devices. What was once a problem in the context of mainframes and departmental minicomputers has spiraled into increasing complexity with the PC, client/server, the Web, mobile devices and now Cloud-based data solutions.

Why is it Happening?  In speaking yesterday with Ravi Shankar Devaraj, Senior Director, Product Marketing, and Dennis Moore SVP & GM of the Master Data Management business unit at Informatica, I learned the following:

The issue of data quality is considered a very high priority in their client base for two primary reasons:

1. Global businesses depend on the quality of data that informs their decisions
2. Increasing numbers of government regulations mandate managing data quality

Because of the Cloud, increasingly users are accessing data across geographies and time zones, making around-the-clock data governance a necessity. Hybrid architectures combining the data stores of Cloud solutions such as salesforce.com and SAP’s on-premises R/3, for example, raise the complexity level of application data integration in a real-time business context.

Market Impact  While data quality and data governance are timely issues, and in the past thirty years a lot of good thinking has gone into shaping the solutions – the Cloud raises the ante significantly by making real-time, around-the-clock, location-independent access to data a business imperative. For global enterprises, the challenge is how to make data governance yield a return on investment, rather than weigh like an unwanted tax on the business units that must comply with policies, procedures, standards, and increasingly, government regulations. Social networks inflect this challenge further by broadening the reach of data, and the information derived from it, and thus raise the premium on data quality.

Find below five key questions that serve as an introduction to our new research agenda focused on data management and the Cloud. Future Strategic Perspectives will drill down into these and other issues further.

1. Why is Data Governance important? Data quality is under continual assault as a large number of forces conspire to duplicate, corrupt, make inconsistent and eventually render meaningless the data that are the essential building blocks of information. Without vigilance, entropy sets in and inevitably degrades data beyond its meaningful use in business decision-making. Multiple systems with differing data definitions, with conflicting formats, with varying values contribute to this, as the need for management control is often considered an unwelcome burden on expedient business practice.
2. Is Data Governance a solution that enterprises can effectively manage? While data governance has been a recurring issue for decades, recent innovations in technology coupled with the new priority being placed on data quality, largely because of the Cloud, have combined to make data governance far more feasible. However, many times the challenges to effective data governance can be traced to multiple data sources in multiple organizational units. Managing data governance across organizational boundaries is the key. This requires executive level commitment and investment that survives changes in management and in project priorities.
3. Is the issue of Data Quality a technology or a methodology issue? Data quality can be achieved through the appropriate combination of technology and methodology. Leading vendors of Master Data Management (MDM) solutions such as IBM, Informatica and Oracle provide advanced technology that has been implemented widely. Hundreds of Informatica customers, for instance, take advantage of its MDM solutions to deliver always-on global data governance. This allows financial services enterprises to deliver data quality improvements with quantifiable business value and also comply with key regulations like the Basel Accords or Dodd-Frank legal entity identifier (LEI).
4. Is a formal, top-down solution workable? Data quality is about both control and access to data. In the former case, control means putting technology and process in place that ensures consistent data practices across systems and across organizational boundaries within an enterprise (and sometimes across enterprise boundaries in inter-organizational business relationships). Both technology and process are necessary to ensure that too much dependence is not placed on people, whose behaviors with respect to data implementation and integration will vary otherwise.
   At the same time, access to data is the whole point of creating and managing quality data. Any MDM solution should be implemented in the context of empowering the use of data in business decision-making and in regulatory contexts, rather than too rigidly constraining data use to ensure its quality. This is a two-pronged approach to data governance that not only improves data quality but makes it more accessible in appropriate business contexts, to traveling executives using mobile devices, for instance.
5. Is Data Governance a cost burden or can it yield a return on investment? Data governance should be approached as a value-creation activity rather than an obligation or necessary cost. We believe, based on work we have done with clients, that there is a return-on-investment case to be made for data governance that can yield high positive returns. This will be discussed in a forthcoming Strategic Perspective that delves deeper into data quality, data governance and the Cloud. Click here to view PDF for this article