The real estate industry has long discussed the importance of data governance. Still, while we all agree it’s critical to data analysis and artificial intelligence functions, the task of assessing and improving data remains daunting.
- How do you start when your organization has data in multiple systems, some of which you may not own?
- How do you change things when everything is in flight?
- How can you quickly find and correct errors and omissions?
- How much will it cost?
DataHealth is a cloud-based solution that allows clients to assess the current state of their data and chart a course to ongoing data quality quickly and easily. When reliable data is used to create information, we believe it can become the transformational foundation for shared knowledge and wisdom in an organization.
What is good data?
There are three ways to look at data:
- Structure: How is your data stored, managed, and moved between systems?
- Information: How complete, correct, and consistent is your data?
- Behavior: How does your business interact with the data?
Within the Information lens, DataHealth can assess your data to determine whether it’s correct, complete, consistent, and compliant.
- Correct: Is the data accurate within its environment?
- Complete: Is the data complete with all its necessary elements?
- Consistent: Is the data consistent across all systems and locations?
- Compliant: Is the data compliant with all the required information contracts, high-order business needs or fund directives?
In this construct, data can be:
- Correct but not complete
- Complete but not correct
- Consistent but consistently wrong
- Complete but not compliant
- … and so on.
This is where DataHealth can help you achieve your information management strategy, data governance and data modeling goals. We start by assessing the completeness of your data or the objects within your data. For example, how many properties have empty address fields? We also provide insights into managing your Yardi data from a sysadmin point of view by looking at how many vendors haven’t had any recent activity, how many users haven’t logged in in months, how many entities are inactive, etc. Once we’ve established your data’s completeness, we examine correctness (Do ZIP codes agree with NCREIF/ MSCI regions?) and consistency (Are proper names capitalized appropriately? Are units the same size month on month).
How does it work?
Clients can choose from a one-time DataHealth system review or a one-year subscription for ongoing, on-demand analysis. DataFreedom will then take a copy of your Yardi database from the existing backup process and analyze it with a number of DataHealth scripts. The resulting dashboards provide a clear picture of your data health, including your overall DataHealth data quality score. You can also drill down to see details and access the underlying Voyager pages to investigate and correct issues. The process is quick and easy, meaning you can begin your data analysis and improvement journey in just 10 days.
Ready to see the results for yourself? Message us in our contact form with “DataHealth Dashboard” and receive an introductory DataHealth dashboard covering one Voyager object (property).
