IBM InfoSphere Information Server is a data integration platform used to understand, cleanse, monitor and transform data. The offerings provide massively parallel processing (MPP) capabilities.
N/A
Informatica Cloud Data Quality
Score 6.8 out of 10
N/A
The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.
N/A
ZoomInfo Operations
Score 8.5 out of 10
N/A
ZoomInfo OperationsOS/RingLead is a comprehensive data quality management platform for sales and marketing operations teams to clean, enrich, and route their go-to-market data.
Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.
For effective data collaboration, systematic verification of customer information, and address, among others, Informatica Data Quality is a fruitful application to consider. Besides, Informatica Data Quality controls quality through a cleansing process, giving the company a professional outline of candid data profiling and reputable analytics. Finally, Informatica Data Quality allows the simplistic navigation of content, with a dashboard that supports predictability.
ZoomInfo Operations is very well suited for bulk record updates, list imports, and record ownership assignments and reassignments. The intuitive user interface makes it easy to explore as many scenarios as possible to use the platform. The platform is extremely powerful as well - the volume of scheduled/automated bulk updates that we have running hourly and daily has never seemed to cause any issues with the system. All expected tasks are completed every time, and if any records couldn't be updated, the system does a great job of highlighting those errors for you. Based on my experience, scenarios that would be less appropriate include automated enrichment, specifically for contacts who may have moved to another company. Also, they need to keep up with Salesforce capabilities regarding what objects can be added as Campaign Members - we have to come up with a workaround when we want to add Accounts to campaigns.
The matching algorithms in IDQ are very powerful if you understand the different types that they offer (e.g., Hamming Distance, Jaro, Bigram, etc..). We had to play around with it to see which best suit our own needs of identifying and eliminating duplicate customers. Setting up the whole process (e.g., creating the KeyGenerator Transformation, setting up the matching threshold, etc..) can be somewhat time consuming and a challenge if you don't first standardize your data.
The integration with PowerCenter is great if you have both. You can either import your mappings directly to PowerCenter or to an XML file. The only downside is that some of the transformations are unique to IDQ, so you are not really able to edit them once in PowerCenter.
The standardizer transformation was key in helping us standardize our customer data (e.g., names, addresses, etc..). It was helpful due to having create a reference table containing the standardized value and the associated unstandardized values. What was great was that if you used Informatica Analyst, a business analyst could login and correct any of the values.
EverString allows us to build account lists based off in-depth firmographic or technographic data. It's far more accurate than trying to build these lists any other way.
EverString is fast. Where it might've previously taken us weeks to build lists of this quality, we now can build them in a matter of minutes (and have them ready to be published in a couple of hours).
As pointed out earlier, due all the robust features IDQ has, our use f the product is successful and stable. IDQ is being used in multiple sources (from CRM application and in batch mode). As this is an iterative process, we are looking to improve our system efficiency using IDQ.
I give this rating because I feel that ZoomInfo has made our work easier and smoother than before. Like now we manage our sales leads, new engagements, easily, and the data we get from ZoomInfo helps us a lot to move in the right direction. Our customer success rate is higher than before after implementing it.
ZommInfo OPerations is pretty intuitive once you get the hang of it. I like that the current integrations make it easier to work within our existing flows and processes. Some of the more advanced features take a bit more training to fully understand and use correctly. And the interface could maybe be updated.
If I talk about the operation's availibility, it is always available whenever I need it. Yeah, once in a while, I have seen an outage, but that was quickly resolved, so I would say they have a strong team that keeps the tool running, no matter if it is updating itself.
I would rate its performance 9. I do not doubt its performance, the pages load quickly withour laging or error. It gives a report within the time frame without errors, no matter how complex the report is. We integrated it with our CRM; at first, it tended to slow a little, but later it was fixed and ran smoothly.
I give this rating because I never feel they deserve less than it. Their commitment towards the customer is outstanding, whenever I need to reach out to the supprot, I feel like I am just talking to a person who is sitting beside me. They respond quickly and solve the problems easily, even guiding us on how not to get into the same problem again and again, so we can avoid going back to support.
Have a plan on how you're going to evaluate. We had a two-month trial period, but a six-month average lead cycle time, making it impossible to evaluate on a purely new-business ROI basis within the trial. We applied the model to our prior data, which demonstrated how much time and effort was devoted to accounts that weren't going to close
IDQ is used by a department at my organisation to ensure and enhance the data quality. The usage was started with address standardization and now it had been brought to altogether a next level of quality check where it fixes duplicates, junk characters, standardize the names, streets, product descriptions. In the past we had issues mainly with duplicate customers and products and this were affecting the sales projection and estimates.
I haven't tried stacking it against any competition as I feel no need to. ZoomInfo blows me away like it first did in 2018, and I don't want something different. I hear Clay is good, but I just haven't felt the need to try it out or replace ZoomInfo at all.
This is the most important and beautiful thing about this tool: it has strong scalability across teams and use cases. It allows us to expand from a single thing to multiple things, like sales to multiple departments, e.g., marketing, Data Accuracy, and Customer Success, without needing complex changes in the setup.
Generate more pipeline - indirectly. Data from anywhere still needs to be transformed and used for a business objective.
Saved time in doing research and data population.
Assuming a business will purchase a data vendor, the comparison between other vendors is a factor of cost, functionality, and data quality. ZoomInfo has higher costs typically - which would lower the ROI - but with proper incentives or discounts, the comparative ROI grows.
