3 Common Entity Resolution Issues & How to Solve Them
Most entity resolution technologies struggle with one or more of these common issues: slow performance, takes too long to add new data sources, or low accuracy levels. It doesn’t have to be that way! Watch this video as Jeff Jonas explains how to solve common entity resolution issues using Senzing® entity resolution which eliminates these common challenges and reduces your stress.
3 Common Entity Resolution Issues & How to Solve Them
1. Entity resolution systems get slower and slower over time
Difficult to increase performance without sacrificing accuracy.
2. Hard to load new data sets into your entity resolution system
Takes too long and requires too much expertise, retraining and retuning.
3. Hard to decrease false positives without reducing accuracy
Endless adjustments to attempt to achieve high levels of accuracy.
Senzing entity resolution eliminates these common issues! You can load data quickly and get high levels of accuracy and fast performance on day one. You can install the Senzing API and evaluate results on your own data in a few hours. Follow Senzing on LinkedIn for more entity resolution videos and blogs.
Video Transcript
Timestamps
0:00 Intro
0:13 Entity Resolution Issue #1: Slowing Speed Over Time
0:27 Entity Resolution Issue #2: Loading Data Sets is Hard
0:37 Entity Resolution Issue #3: Maintaining Accuracy While Removing False Positives
0:55 Senzing Entity Resolution is Fast, Self-Tuning, Self-Learning
1:15 Real-Time Transactional Continuous Entity Resolution
Three common stressful points that might lead one to think they want to take a quick look at Senzing.
0:13 Entity Resolution Issue #1: Slowing Speed Over Time
One: your entity resolution is getting slower and slower over time. You’re thinking to yourself, we’re going to have to figure out how to speed this up and not lose any accuracy.
0:27 Entity Resolution Issue #2: Loading Data Sets is Hard
Two: every time you bring a new data set and say let’s load this, it’s very hard. The amount of time it takes, the expertise, the re-training, and the re-tuning.
0:37 Entity Resolution Issue #3: Maintaining Accuracy While Removing False Positives
And the third thing you might be noticing is it’s getting pretty hard to get the false positives out without killing the overall accuracy of the system. It’s like moving that little bead, you move it this way too far to get the false positive down, you’re missing a whole bunch of good stuff. It’s that endless struggle on accuracy.
0:55 Senzing Entity Resolution is Fast, Self-Tuning, Self-Learning
Senzing allows you to load data really fast. It allows you to get rid of those false positives and false negatives in an unprecedented way because it’s self-tuning, self-learning, out-of-the-box. It will outperform probably what you’re doing custom, and it’s going to scale up and it doesn’t get slower and slower and slower and slower.
1:15 Real-Time Transactional Continuous Entity Resolution
That’s really unique because it’s a real-time transactional [entity resolution] system that’s continuous, so you load it once and then just stay current. Uses very little compute.
So, if you’re struggling with things like solving common entity resolution issues like slow performance, there’s a quick fix. [It’s] not a Band-Aid – it’s like a quick real fix. You’ll find [Senzing] installs really easy. You’ll find you can audit it against your own data really fast, all in the same week. You can probably integrate it in a few weeks, under a month or two, and be in production and just leapfrog all your competitors and take out a bunch of cost. Check out our Senzing API.