For the last couple of years, the Zeenea international sales team has been in contact with prospective clients the world over, presenting Zeenea, running product demos, submitting RFPs (mostly against the big guns in the industry), advising CDOs on data management strategies, accompanying existing customers with their catalog deployment, helping address technical challenges when they arise and always discussing pricing…
Anyone who has been actively in the market for data catalogs, pricing will feel like a complex affair which varies widely depending on use cases, providers (SaaS, On-prem, annual subscription etc.), number of users, etc.
This blog post seeks to demonstrate that putting a price tag on a data catalog should not really be a complex affair and while the technology that makes a catalog tick can be quite impressive (especially if its powered by a knowledge graph), its ultimate purpose is to help data users access, curate and leverage information that already exists. Nothing more nothing less.
Below, we’ll relate a couple of fairly typical examples of Zeenea’s approach to pricing which resulted in customer wins for us, and money saved for the customer.
Avoid the quagmire of maximum cost/minimal adoption.
One telling example of the financial repercussions of mismanaged data catalog adoption occurred with a large French bank (Zeenea is a Paris-based startup).
This bank had initially chosen a well known data catalog provider to help with the management, governance and quality of their data. Like all financial institutions, this one was subject to BCBS 239 and compliance was therefore a key issue. The catalog provider, whose platform boasts a very sophisticated predefined metamodel with tons of features, therefore set out to help the customer organize its data governance around BCBS 239. Unfortunately, the project quickly began to turn sour for a couple of reasons:
1- The “out of the box” metamodel, it turned out, didn’t readily fit with the organization of the data teams. The predictable consequence of this mismatch was having to allocate far more internal resources than planned to handle their compliance initiative.
2- The focus on Data Governance didn’t really deal with the needs of business teams looking for easy access to their datasets. This unhappy situation had a negative impact on the overall adoption of the data catalog and end users simply stopped using it.
By the time the client stopped the initiative, there were a very limited number of compliance experts actually using the catalog for a bill of a few million euros per year…Suffice it to say that the purse holders were not entirely satisfied with the cost-benefit ratio…
The lesson here is that in order to successfully implement a data catalog long term, one needs early and durable user adoption. A simple, well defined, use case with a manageable number of stakeholders will go a long way to achieving that whilst ensuring costs are kept within reasonable limits. This is precisely what Zeenea did with this customer.
The bill was reduced 10 fold and catalog adoption of our Explorer platform tripled.
Don’t crack a walnut with a (costly) sledgehammer.
Another customer (an SME from the UK in the retail sector), whose data landscape consists of a BI tool, PostgresQL, an ETL platform and PowerBI, reached out to us having already received quotes from other well established data catalog providers.
Their use case was straightforward: The data engineering team needed to clean up their data lake after years of neglect and the data users in the group, analytics folk mostly, wanted to access data assets more easily.
I’m paraphrasing but the overriding sentiment was that the solutions they had looked at before consulting Zeenea, whilst undoubtedly useful for larger organisations with complex data landscapes, data governance and compliance imperatives, had too many features which were irrelevant to their actual requirements.
The customer was eventually sent a 6 figure quote which the CFO promptly discarded.
Today this mismatch is the most common one we come across, especially amongst small data teams with more straightforward use cases for a data catalog. Unlike the French bank mentioned above, most SMEse cannot afford to spend, let alone lose, vast amounts of money on a failed data experiment.
So how much should a data catalog really cost…?
Early in 2020, we decided to take a different approach to pricing, one that was coherent with our “Start small, Scale fast” approach to data cataloging adoption. This pricing model, presented as a “Basic Data Discovery”, was designed to encourage data teams to start their data cataloging journey with a straightforward use case, roll out the catalog to other users/projects incrementally, thus ensuring maximum catalog adoption and, crucially, keep a handle on cost.
Our basic Data Discovery conditions are simple (and easy to deliver on) – This offer includes the POC, 2 connectors, 2 data stewards, 20 data explorers and of course customer support.
Provide us with…
- A Use Case for the POC.
- The Data sources you need to connect to (up to 2 for the Basic Data Discovery).
- The number of Data Stewards needed (up to 2 for the Basic Data Discovery).
- The number of Data Explorers needed (up to 20 for the Basic Data Discovery).
…and Zeenea will provide you with a quote your CFO can depend on. It really is that simple.*
*These conditions were not chosen at random. In our experience, data teams looking to roll out a cataloging solution seldom choose a use case requiring more than 2 data connectors and a handful of data stewards, and we don’t necessarily recommend that they do.