So you’re tasked with your organization’s next big data migration. Maybe you’re moving to a new CRM system. Maybe you’ve just acquired another company and need to integrate their data into your system. Whatever the reason, data migrations are critical processes that many businesses go through. The continuing explosion in the volume of data businesses collect, store and use suggests that the trend of most companies engaging in some data migration project isn’t letting up anytime soon. According to a recent data migration study, 91% of companies engage in data migration projects.
Whether you’re working on a large data migration project, or simply trying to answer business questions with your data and having issues, Experian Pandora should be part of the conversation. We often hear from customers that they have disparate databases, leverage excel to house important data, or just have no idea how bad their data really is. This often leads to us running data tests on a subset of their data, which typically cannot tell the whole story, or is not statistically significant based on the total size of their database.
Government agencies at every level—city, state, and federal—collect large amounts of data; that’s a fact. The challenge for many lies in the ways information is collected and processed. Much of it is locked up in departmental silos, on somewhat dated computer systems, and it’s hard to access for additional analysis or to share publicly. Much of it may have been collected on paper forms or input by busy staff with lots of other things to do. Yet in any commercial organization, your data might be considered like gold dust! Locked within those siloed systems are many nuggets of valuable information that can help improve the efficiency of your entire organization, help deliver better services, and help improve the lives of your constituents.
It’s 8:30 in the morning on Day 3 of the MDM & Data Governance conference and Aaron Zornes, Chief Research Officer of The MDM Institute, is about to introduce a panel of three experts who will address an intimate room of 100 or so attendees.
Extract, transform, and load (ETL) is the process of integrating data from multiple, typically disparate, sources and bringing them together into one central location. It is a key component to businesses successfully making use of data in a data warehouse.
Sure, the process itself is fairly straightforward, and when done right, ETL prepares an organization for powerful business intelligence initiatives. However, a lot goes into a successful ETL process. Let’s discuss the three steps involved and why data management practices are an essential foundation to carrying ETL out properly.
Affectionately dubbed ‘The Catalina Wine Mixer’ for many years by Experian Data Quality employees who have attended, CS Week 2017 certainly lived up to its reputation as being the biggest event of the year. This year’s conference took place in San Antonio, Texas and centered around customer service within the electric, gas and water/wastewater utility industries. The event drew a crowd of about 2,000 utilities professionals from all over the United States and Canada.
This year the American Association of Motor Vehicle Administrators (AAMVA) took their Annual International Conference (AIC) to Williamsburg, Virginia. AIC showcases the latest trends in the motor vehicle and law enforcement community and provides a forum for chief administrators to learn from and network with their fellow jurisdiction executives. This is one of my favorite events that Experian Data Quality sponsors, and this year did not disappoint.
Recently, we discussed the dilemma of building a data management program and compared the process to building a house. This proved very insightful, as it laid the foundation for a complex and sometimes overwhelming topic: developing a data management methodology.
In my blog, “The role of technology in empowering the CIO and CDO office”, I explain the role the Chief Information Officer can play in helping the Chief Data Officer function through technology supporting data preparation, monitoring and data governance. Technology is not the answer to all of these, however it can make data practitioners lives much easier, providing the necessary productivity boost.
When you decide to take on a data integration project, it will require a lot of advanced planning, work, time and resources. Without a deep understanding of what the project's requirements, it's unlikely that you will complete the integration on time and on budget. Yesterday, Rishi Patel, Strategic Account Manager at Experian Data Quality and Michael Ott, Senior Vice President at Innovative Systems, Inc., an Experian Data Quality partner, presented a webinar, “De-risking data integration projects.” The webinar focused on four major topics: the historical challenges of data integration projects, how current environments introduce additional complexity, an advanced methodology for overcoming data integration challenges, and a checklist to ensure that your project stays on track for success.
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