Data integration is fast becoming one of the most pressing issues in enterprise applications. At the same time, integrations are becoming easier—and that is part of the problem.
Image yourself in this situation: that shiny new expense management application you installed is the best thing your outside sales reps have ever seen. The vendor provided a plug-in connector for data integration that took only a few minutes to connect to your system of record. Everybody is happy.
Except that your CIO has another one-off data connection to add to the hundreds or thousands IT already tries to manage. They don’t have enough staff to stop, take a breath, and organize them.
So, off you go to find a single solution to manage all your data streams. Then you find there are so many ways to do it you don’t know where to begin. And if you send your CIO out to find the right solution for everybody, it’s like sending Dad out to buy a prom dress. You can be sure of getting a workable solution, but no one will be happy. With the growth of cloud applications, business users have become accustomed to buying their preferred solutions.
Businesses generate a torrent of information, and business leaders demand that their systems collect, store, and present that data in a way that helps them make better business decisions. Not only do we generate more and larger internal data streams, but we also exchange data with our partners, suppliers, distribution channels, regulatory agencies, and more.
Batch transfers of yesterday’s data are no longer enough. People need real-time data to make decisions. Data needs are outstripping the capabilities of data warehousing and ETL operations, and technology is racing to stay ahead. Old methods are no longer enough.
Cloud talent management platforms and customer relationship management (CRM) have matured to the point that they interact with many other enterprise systems. To understand the impact of talent management practices, people need access to financial, production, and organizational performance data.
Logistics operations that run on a vast installed base of batch Electronic Data Interchange (EDI) integrations now need to provide real-time information to e-commerce applications and CRM. E-commerce applications that promise two-hour delivery need to know exactly where inventory is at the moment a customer places an order.
Business leaders can no longer turn everything over to IT and forget about it. Nor is It sufficient to throw it all into a data lake and let a vendor sort it out for you. Data management must now be a core strategic activity with an enterprise-wide focus. How your organization creates, stores, delivers, and consumes data is integral to business execution and strategy.
At the core of this effort is data governance and master data management. Data governance is “the exercise of decision-making and authority for data-related matters.” It is an organizational function that manages how information is created, collected, processed and manipulated, stored, and used.[1] Master data management (MDM) refers to a system of managing the data of an enterprise using a common point of reference.[2]
Our recommendation is to start a serious conversation about governance and data management. There are many solutions, and no single solution will handle all your data needs. It will take a careful navigation of needs assessment, potential technology solutions, and price points to find the solution mix that will address your needs.
Finding the answer begins with asking the right question. First, build the governance structure to manage enterprise-wide data management. Then, ask the right questions: who uses what data, and where, when, how, and why.
References :
1. "The Basic Information - The DGI." The Data Governance Institute. Accessed November 03, 2016.
2. "What Is a Master Data Management System?" TechTarget. Accessed November 03, 2016.
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