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.
Organizations everywhere are looking to do more with their data assets, as well as better leverage open data and third party data sources for additional consumer insight. The good news is that there is no shortage of information available. The bad news is that wrangling and making sense of all that information can be very challenging. That is why we see 61 percent of U.S. companies stating inaccurate data is undermining their ability to provide an excellent customer experience.
According to a new Experian Data Quality report, Investing in digital transformation: This year’s most sought-after data roles, businesses are hiring a mix of business- and regulation-focused data positions. Below is a chart showing the top roles being hired according to U.S. respondents and also c-level executives specifically.
Beep! Beep! The American Association of Motor Vehicle Administrators (AAMVA) held their Region I Conference this week in Portland, Maine. Thought leaders and industry professionals seized the opportunity to network with each other, learn best practices from affiliate agencies, and share insights on what’s to come in the continually evolving world of motor vehicle administration and public safety. Portland, Maine provided a beautiful backdrop to the week, especially as conference attendees set sail on a sunset ferry cruise to Peak’s Island for a lobster dinner!
In today’s data-driven world, you will hear buzzwords thrown around like MDM, big data, machine learning, data lakes, etc. But then you may think, how exactly do these concepts apply to my organization and my specific role? How can I deploy the most valuable data management processes? To answer these questions, it is important to understand what modern data management looks like at a high level, and then how are businesses are using modern data management to refine business processes and enable best practices. Understanding the concept of modern data management is the first step in deciding how to enable it in your organization.
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.
When it comes to storing and accessing information for an organization, there are several processes involved to help users get the data they need in a timely fashion. As one of the most valuable business assets, managing data and leveraging it to improve business operations is of paramount importance. As more and more business decisions become data-driven, organizations continue to place greater emphasis on effectively managing their data. Since most processes are now informed by data and constantly monitored, it’s easy to see how process management and data management go hand in hand. But has it always been that way? Not exactly.
As a Health and Human Services provider, you know how important health is. Connecting people with the resources they need to improve their lives is a top priority. But do you ever consider the health of your organization? The same way that healthy people enjoy fuller lives, healthy organizations are better able to provide their constituents with excellent services. In order to make the right strategic decisions, you need your data to be healthy too. So what does it mean to have healthy data and how can you make sure you do?
It is no secret that the financial industry is completely changing the way that it functions. Financial institutions are expected to have a comparable user experience to retailers, and at the same time continue to uphold regulatory compliance. It is important for financial organizations to understand what steps are necessary in satisfying these marketplace essentials. The more they are able to balance and prioritize compliance and providing a frictionless and automated experience for customers, the more financial institutions are able to remain competitive in a changing industry.
We’ve all heard the saying “you are what you eat” in reference to our morning donut and coffee. But did you ever consider that the same principle applies to your organization’s data collection processes? Much like the saturated fats from bad-for-you food that clog up your arteries, unchecked bad data can enter your database and compromise your ability to draw on that information in the future. That’s why it’s important to put measures in place to validate and correct bad data at every point of entry. Before your database has a cardiac event (and increases your stress levels), let’s talk about your data’s diet.
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